Triple
T10277920
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bilecik Province |
E241016
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
İnhisar
İnhisar is a small town and district located in Turkey's Bilecik Province in the Marmara region.
|
E862744
|
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: İnhisar | Statement: [Bilecik Province, contains, İnhisar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: İnhisar Context triple: [Bilecik Province, contains, İnhisar]
-
A.
Doğanhisar
Doğanhisar is a rural district and town in central Turkey known for its agricultural economy and location within the Konya region.
-
B.
Darıca
Darıca is a coastal town and district in northwestern Turkey, situated on the Sea of Marmara and known for its zoo, recreation areas, and proximity to Istanbul.
-
C.
Güzelyurt
Güzelyurt is a town in the northwestern part of Cyprus, known for its citrus orchards and archaeological sites.
-
D.
Orlu
Orlu is a prominent town and commercial hub in southeastern Nigeria that serves as an important center for trade, industry, and regional administration.
-
E.
Zeytinburnu
Zeytinburnu is a densely populated working- and middle-class district on Istanbul’s European side, known as an early industrial area and a key transport hub within the city.
- 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: İnhisar Triple: [Bilecik Province, contains, İnhisar]
Generated description
İnhisar is a small town and district located in Turkey's Bilecik Province in the Marmara region.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: İnhisar Target entity description: İnhisar is a small town and district located in Turkey's Bilecik Province in the Marmara region.
-
A.
Doğanhisar
Doğanhisar is a rural district and town in central Turkey known for its agricultural economy and location within the Konya region.
-
B.
Darıca
Darıca is a coastal town and district in northwestern Turkey, situated on the Sea of Marmara and known for its zoo, recreation areas, and proximity to Istanbul.
-
C.
Güzelyurt
Güzelyurt is a town in the northwestern part of Cyprus, known for its citrus orchards and archaeological sites.
-
D.
Orlu
Orlu is a prominent town and commercial hub in southeastern Nigeria that serves as an important center for trade, industry, and regional administration.
-
E.
Zeytinburnu
Zeytinburnu is a densely populated working- and middle-class district on Istanbul’s European side, known as an early industrial area and a key transport hub within the city.
- 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_69d381a94c1881908fc38fc263d9b9c2 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d29f0cf08190a2c5e7523d5c731e |
completed | April 7, 2026, 9:47 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d87e40205c8190a4788e1db1f149d2 |
completed | April 10, 2026, 4:36 a.m. |
| NEDg | Description generation | batch_69d8837e70508190b03e8983b2617eac |
completed | April 10, 2026, 4:58 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d889cc40648190a1d80b955e676ea5 |
completed | April 10, 2026, 5:25 a.m. |
Created at: April 6, 2026, 11:37 a.m.