Triple
T9542575
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mary Region |
E230193
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object |
Bayramaly
Bayramaly is a city in southeastern Turkmenistan known as a regional center near the ancient ruins of Merv and for its hot desert climate.
|
E805784
|
NE FINISHED |
How this triple was built (4 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Bayramaly | Statement: [Mary Region, hasCity, Bayramaly]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bayramaly Context triple: [Mary Region, hasCity, Bayramaly]
-
A.
Bayramiç
Bayramiç is a town and district in Turkey’s Çanakkale Province, known for its agricultural production and proximity to the Kaz Mountains (Mount Ida).
-
B.
Karatay
Karatay is a central district and municipality within Turkey’s Konya Province, known for its historical sites and role in the urban core of Konya city.
-
C.
Balykchy
Balykchy is a town in Kyrgyzstan located at the western end of Lake Issyk-Kul, serving as a key transport and gateway hub for the region.
-
D.
Bayrampaşa
Bayrampaşa is a densely populated working- and middle-class district on Istanbul’s European side, known for its major transport links, industrial areas, and large bus terminal.
-
E.
Gaziemir
Gaziemir is a district of İzmir, Turkey, known for its proximity to the city’s main international airport and its role as a growing residential and commercial hub.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Bayramaly Triple: [Mary Region, hasCity, Bayramaly]
Generated description
Bayramaly is a city in southeastern Turkmenistan known as a regional center near the ancient ruins of Merv and for its hot desert climate.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Bayramaly Target entity description: Bayramaly is a city in southeastern Turkmenistan known as a regional center near the ancient ruins of Merv and for its hot desert climate.
-
A.
Bayramiç
Bayramiç is a town and district in Turkey’s Çanakkale Province, known for its agricultural production and proximity to the Kaz Mountains (Mount Ida).
-
B.
Karatay
Karatay is a central district and municipality within Turkey’s Konya Province, known for its historical sites and role in the urban core of Konya city.
-
C.
Balykchy
Balykchy is a town in Kyrgyzstan located at the western end of Lake Issyk-Kul, serving as a key transport and gateway hub for the region.
-
D.
Bayrampaşa
Bayrampaşa is a densely populated working- and middle-class district on Istanbul’s European side, known for its major transport links, industrial areas, and large bus terminal.
-
E.
Gaziemir
Gaziemir is a district of İzmir, Turkey, known for its proximity to the city’s main international airport and its role as a growing residential and commercial hub.
- F. None of above. chosen
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69ca847c70b8819088a0a0bad64a50d6 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd98e9be048190bf1f01884ff7c362 |
completed | April 1, 2026, 10:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d14c6538b08190a9f81304214a876d |
completed | April 4, 2026, 5:37 p.m. |
| NEDg | Description generation | batch_69d14d44b7f08190b66fecb315b37535 |
completed | April 4, 2026, 5:41 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d14e0823e881908ed723d20f14789b |
completed | April 4, 2026, 5:44 p.m. |
Created at: March 30, 2026, 8:01 p.m.