Triple
T15659894
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hecatompylos |
E376540
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Damghan |
E788417
|
NE FINISHED |
How this triple was built (2 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: Damghan | Statement: [Hecatompylos, locatedNear, Damghan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Damghan Context triple: [Hecatompylos, locatedNear, Damghan]
-
A.
Damghan
chosen
Damghan is an ancient city in north-central Iran known for its historical monuments and archaeological sites, including one of the oldest mosques in the country.
-
B.
Margilan
Margilan is a historic city in eastern Uzbekistan renowned as a traditional center of silk production and trade along the Silk Road.
-
C.
Ardestan
Ardestan is an ancient city in central Iran known for its historic architecture, including notable mosques and traditional urban fabric.
-
D.
Bavanat
Bavanat is a small city in southern Iran known for its traditional rural landscapes, gardens, and location within the mountainous region of Fars Province.
-
E.
Andimeshk
Andimeshk is a city in southwestern Iran known as a regional transportation hub and gateway to the Zagros Mountains.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d85cd1564c8190991adda63bfab4b0 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04ef4e6a08190ad8bbafaa3612f22 |
completed | April 16, 2026, 2:52 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a000777c6a08190a4deed9952179be5 |
completed | May 10, 2026, 4:20 a.m. |
Created at: April 10, 2026, 4:15 a.m.