Triple
T16138803
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bhiwani district |
E391598
|
entity |
| Predicate | hasUrbanCentre |
P11388
|
FINISHED |
| Object | Bhiwani city |
E1201003
|
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: Bhiwani city | Statement: [Bhiwani district, hasUrbanCentre, Bhiwani city]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bhiwani city Context triple: [Bhiwani district, hasUrbanCentre, Bhiwani city]
-
A.
Bhiwani
chosen
Bhiwani is a city in the Indian state of Haryana known as a regional educational and political hub.
-
B.
Rewari
Rewari is a historic city in the Indian state of Haryana, located near Delhi and known for its brass industry and strategic position in northern India.
-
C.
Saharanpur
Saharanpur is a city in the Indian state of Uttar Pradesh known as a commercial and transportation hub, particularly for its wood carving industry and agricultural trade.
-
D.
Yamunanagar
Yamunanagar is an industrial city in the Indian state of Haryana, known for its plywood, paper, and metal industries and its proximity to the Yamuna River.
-
E.
Bhiwani district
Bhiwani district is an administrative district in the Indian state of Haryana, known for its agricultural economy and prominence in boxing and other sports.
- 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_69d87f1bb0988190b490d273dbf3fd03 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e21a06e0988190b5cd62d422d058a2 |
completed | April 17, 2026, 11:31 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a009d25abec8190954b640b63efa0c2 |
completed | May 10, 2026, 2:58 p.m. |
Created at: April 10, 2026, 5:01 a.m.