Triple
T6531835
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Khuzestan |
E152248
|
entity |
| Predicate | containsCity |
P294
|
FINISHED |
| Object |
Andimeshk
Andimeshk is a city in southwestern Iran known as a regional transportation hub and gateway to the Zagros Mountains.
|
E610074
|
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: Andimeshk | Statement: [Khuzestan, containsCity, Andimeshk]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Andimeshk Context triple: [Khuzestan, containsCity, Andimeshk]
-
A.
Margilan
Margilan is a historic city in eastern Uzbekistan renowned as a traditional center of silk production and trade along the Silk Road.
-
B.
Kazerun
Kazerun is a historic city in southwestern Iran known for its proximity to the ancient ruins of Bishapur and its cultural significance within Fars Province.
-
C.
Bijar
Bijar is a town in Iran renowned for producing exceptionally durable, densely knotted Persian carpets known for their rich colors and intricate designs.
-
D.
Firuzabad
Firuzabad is a historic city in Iran renowned for its Sassanian-era archaeological sites and distinctive circular urban plan.
-
E.
Aliabad
Aliabad is a small town in northern Pakistan that serves as the main commercial and administrative center of the Hunza Valley in Gilgit-Baltistan.
- 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: Andimeshk Triple: [Khuzestan, containsCity, Andimeshk]
Generated description
Andimeshk is a city in southwestern Iran known as a regional transportation hub and gateway to the Zagros Mountains.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Andimeshk Target entity description: Andimeshk is a city in southwestern Iran known as a regional transportation hub and gateway to the Zagros Mountains.
-
A.
Margilan
Margilan is a historic city in eastern Uzbekistan renowned as a traditional center of silk production and trade along the Silk Road.
-
B.
Kazerun
Kazerun is a historic city in southwestern Iran known for its proximity to the ancient ruins of Bishapur and its cultural significance within Fars Province.
-
C.
Bijar
Bijar is a town in Iran renowned for producing exceptionally durable, densely knotted Persian carpets known for their rich colors and intricate designs.
-
D.
Firuzabad
Firuzabad is a historic city in Iran renowned for its Sassanian-era archaeological sites and distinctive circular urban plan.
-
E.
Aliabad
Aliabad is a small town in northern Pakistan that serves as the main commercial and administrative center of the Hunza Valley in Gilgit-Baltistan.
- 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_69c688048ec8819093a47f7d332e12ec |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6adbcf820819097ca33a5fc14fd64 |
completed | March 27, 2026, 4:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6eed0ef548190b384e37f39830b14 |
completed | March 27, 2026, 8:55 p.m. |
| NEDg | Description generation | batch_69c6f09ea58c8190bfd8a183581b5a5a |
completed | March 27, 2026, 9:03 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c6f1a0935881908afc30ce76bdf76f |
completed | March 27, 2026, 9:07 p.m. |
Created at: March 27, 2026, 1:46 p.m.