Triple
T20412264
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Salasar Balaji |
E500613
|
entity |
| Predicate | hasNearbyCity |
P350
|
FINISHED |
| Object | Sujangarh |
—
|
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: Sujangarh | Statement: [Salasar Balaji, hasNearbyCity, Sujangarh]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sujangarh Context triple: [Salasar Balaji, hasNearbyCity, Sujangarh]
-
A.
Sujangarh
chosen
Sujangarh is a town in the Indian state of Rajasthan known for its local markets, temples, and role as a regional commercial center.
-
B.
Arjan Garh
Arjan Garh is an elevated station on the Delhi Metro network serving the southern outskirts of Delhi near the Haryana border.
-
C.
Surajgarh
Surajgarh is a town in the Jhunjhunu district of Rajasthan, India, known for its historic havelis and traditional Rajasthani architecture.
-
D.
Kishangarh
Kishangarh is a town and legislative assembly constituency in Rajasthan, India, known for its marble industry and distinctive miniature paintings.
-
E.
Naraingarh
Naraingarh is a town in the northern Indian state of Haryana, known for its agricultural surroundings and role as a local commercial center.
- 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_69e0b4a935588190b9446a99b37ced44 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e67a3f8fdc8190b05b6c41b38f34b7 |
completed | April 20, 2026, 7:10 p.m. |
Created at: April 16, 2026, 11:30 a.m.