Triple
T23238653
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jhabua district |
E581373
|
entity |
| Predicate | hasCapital |
P204
|
FINISHED |
| Object | Jhabua |
—
|
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: Jhabua | Statement: [Jhabua district, hasCapital, Jhabua]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jhabua Context triple: [Jhabua district, hasCapital, Jhabua]
-
A.
Jhabua
chosen
Jhabua is a town and administrative district headquarters in western Madhya Pradesh, India, known for its significant tribal population and culture.
-
B.
Jambusar
Jambusar is a town in the Bharuch district of Gujarat, India, known for its historical significance and regional trade and agriculture.
-
C.
Bhopalgarh
Bhopalgarh is a town in the Indian state of Rajasthan, known for its rural setting and administrative role within the region.
-
D.
Dabhoi
Dabhoi is a historic town in the Indian state of Gujarat, known for its ancient fortifications and architectural heritage.
-
E.
Alirajpur
Alirajpur is a town and district headquarters in western Madhya Pradesh, India, known for its predominantly tribal population and vibrant indigenous culture.
- 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_69e2460556f88190be1744a84a84173f |
completed | April 17, 2026, 2:39 p.m. |
| NER | Named-entity recognition | batch_69f192ebaef4819083a7805537ad993f |
completed | April 29, 2026, 5:11 a.m. |
Created at: April 17, 2026, 4:10 p.m.