Triple
T21188593
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Karauli district |
E522151
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object | Karauli |
—
|
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: Karauli | Statement: [Karauli district, hasCity, Karauli]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Karauli Context triple: [Karauli district, hasCity, Karauli]
-
A.
Karauli
chosen
Karauli is a historic town and pilgrimage center in the Indian state of Rajasthan, known for its ancient temples and distinctive red sandstone architecture.
-
B.
Laxmangarh
Laxmangarh is a town in the Sikar district of Rajasthan, India, known for its historic fort, havelis, and traditional Rajasthani architecture.
-
C.
Laxmangarh
Laxmangarh is a town in the Alwar district of Rajasthan, India, known for its local markets and surrounding agricultural communities.
-
D.
Narsinghgarh
Narsinghgarh is a historic town in central India that once served as the administrative and cultural center of the former princely Narsinghgarh State.
-
E.
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.
- 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_69e0b51061388190aa03f19700d3ef04 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e7333403448190bcd9cc0805e414b5 |
completed | April 21, 2026, 8:20 a.m. |
Created at: April 16, 2026, 3:07 p.m.