Triple
T12805679
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bathinda |
E306137
|
entity |
| Predicate | hasFort |
P3479
|
FINISHED |
| Object | Qila Bahadurgarh |
E342152
|
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: Qila Bahadurgarh | Statement: [Bathinda, hasFort, Qila Bahadurgarh]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Qila Bahadurgarh Context triple: [Bathinda, hasFort, Qila Bahadurgarh]
-
A.
Sujangarh
Sujangarh is a town in the Indian state of Rajasthan known for its local markets, temples, and role as a regional commercial center.
-
B.
Bahadurgarh
chosen
Bahadurgarh is a rapidly developing city in the Indian state of Haryana that forms part of the urban agglomeration surrounding Delhi.
-
C.
Arjan Garh
Arjan Garh is an elevated station on the Delhi Metro network serving the southern outskirts of Delhi near the Haryana border.
-
D.
Kishangarh
Kishangarh is a town and legislative assembly constituency in Rajasthan, India, known for its marble industry and distinctive miniature paintings.
-
E.
Surajgarh
Surajgarh is a town in the Jhunjhunu district of Rajasthan, India, known for its historic havelis and traditional Rajasthani architecture.
- 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_69d7bdf366888190a8cccb982606889c |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96e7f370c8190b3fc39c1b63394c6 |
completed | April 10, 2026, 9:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6e25f2c8481908ca9784a8e643a28 |
completed | May 3, 2026, 5:51 a.m. |
Created at: April 9, 2026, 5:31 p.m.