Triple
T19083551
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Najafgarh |
E467086
|
entity |
| Predicate | nearbyCity |
P350
|
FINISHED |
| Object | Bahadurgarh |
—
|
NE NERFINISHED |
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: Bahadurgarh | Statement: [Najafgarh, nearbyCity, Bahadurgarh]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bahadurgarh Context triple: [Najafgarh, nearbyCity, Bahadurgarh]
-
A.
Bahadurgarh
chosen
Bahadurgarh is a rapidly developing city in the Indian state of Haryana that forms part of the urban agglomeration surrounding Delhi.
-
B.
Mahendragarh
Mahendragarh is a town and district headquarters in the northern Indian state of Haryana.
-
C.
Anupgarh
Anupgarh is a town in the Ganganagar district of Rajasthan, India, known for its agricultural surroundings and proximity to the India–Pakistan border.
-
D.
Sardulgarh
Sardulgarh is a town in the Mansa district of Punjab, India, known for its agricultural economy and location near the Punjab–Haryana border.
-
E.
Ramgarh
Ramgarh is a town and administrative district headquarters in the Indian state of Jharkhand, known for its coal mining and industrial activities.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8dd04f4488190b1121cc53ef2bfd6 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5e34600f88190bd96bcc2c5c08d14 |
completed | April 20, 2026, 8:26 a.m. |
Created at: April 10, 2026, 12:04 p.m.