Triple
T13835099
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mahoba district |
E332504
|
entity |
| Predicate | containsTown |
P847
|
FINISHED |
| Object | Charkhari |
E1064600
|
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: Charkhari | Statement: [Mahoba district, containsTown, Charkhari]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Charkhari Context triple: [Mahoba district, containsTown, Charkhari]
-
A.
Charkhari
chosen
Charkhari is a legislative assembly constituency in the Mahoba district of Uttar Pradesh, India.
-
B.
Chakia
Chakia is a town in the East Champaran district of the Indian state of Bihar, known primarily as a local administrative and market center for the surrounding rural region.
-
C.
Chikaranga
Chikaranga is an alternative name for the Karanga language, a major Shona dialect spoken primarily in southern Zimbabwe.
-
D.
Bawarchi
Bawarchi is a 1972 Hindi comedy-drama film directed by Hrishikesh Mukherjee, known for its heartwarming story about a mysterious cook who transforms a quarrelsome joint family.
-
E.
Bhokar
Bhokar is a legislative assembly constituency in the Nanded district of Maharashtra, India.
- 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_69d81c5ae7c88190b0dd41bdafeb5999 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de029b352081909605baaedc336213 |
completed | April 14, 2026, 9:02 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7c0ed7e8c81909ffed37f5b097188 |
completed | May 3, 2026, 9:41 p.m. |
Created at: April 9, 2026, 10:13 p.m.