Triple
T13958620
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jalore district |
E335731
|
entity |
| Predicate | hasHeadquarters |
P62
|
FINISHED |
| Object | Jalore |
E335731
|
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: Jalore | Statement: [Jalore district, hasHeadquarters, Jalore]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jalore Context triple: [Jalore district, hasHeadquarters, Jalore]
-
A.
Jalore
chosen
Jalore is a historic town and district headquarters in the Indian state of Rajasthan, known for its ancient fort and role in the Marwar region’s history.
-
B.
Sirohi
Sirohi is a town in the Indian state of Rajasthan known for its historical significance and role as the former seat of a princely state.
-
C.
Pratapgarh
Pratapgarh is a town in the Indian state of Rajasthan known for its historical association with the Mewar region and its distinctive tribal culture and handicrafts.
-
D.
Jhunjhunu
Jhunjhunu is a city and district in the northeastern part of Rajasthan, India, known for its historic havelis, rich Marwari heritage, and role as a prominent center of education and military recruitment.
-
E.
Bhilwara
Bhilwara is a prominent industrial city in the Indian state of Rajasthan, known especially for its large textile and garment manufacturing sector.
- 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_69d81c61f3508190aaf2ca0dc0002c59 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2e7a34f08190aa0d88b66154f268 |
completed | April 14, 2026, 12:09 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd323e89948190bb280e93e2058c0a |
completed | May 8, 2026, 12:45 a.m. |
Created at: April 9, 2026, 10:17 p.m.