Triple
T12320706
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Laxmangarh |
E293719
|
entity |
| Predicate | hasNearbyCity |
P350
|
FINISHED |
| Object | Jhunjhunu |
E822588
|
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: Jhunjhunu | Statement: [Laxmangarh, hasNearbyCity, Jhunjhunu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jhunjhunu Context triple: [Laxmangarh, hasNearbyCity, Jhunjhunu]
-
A.
Jhunjhunu
chosen
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.
-
B.
Bikaner
Bikaner is a historic city in the Indian state of Rajasthan, known for its desert landscape, grand forts, and rich Rajasthani culture.
-
C.
Jalore
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.
-
D.
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.
-
E.
Kaithal
Kaithal is a historic town in the Indian state of Haryana, known for its medieval heritage and association with the Delhi Sultanate.
- 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_69d6ab6ae0dc8190b1522a9c1c55c114 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d93f4c2b548190938fff9427f07dc7 |
completed | April 10, 2026, 6:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f746055aac81909626eaa891199019 |
completed | May 3, 2026, 12:56 p.m. |
Created at: April 8, 2026, 9:53 p.m.