Triple
T22528578
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jalna |
E556970
|
entity |
| Predicate | connectedTo |
P37
|
FINISHED |
| Object | Jalgaon |
—
|
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: Jalgaon | Statement: [Jalna, connectedTo, Jalgaon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jalgaon Context triple: [Jalna, connectedTo, Jalgaon]
-
A.
Jalgaon
chosen
Jalgaon is a city in northwestern Maharashtra, India, known as a major commercial center for banana production and trade.
-
B.
Sarangpur
Sarangpur is a prominent town and commercial center in the Malwa region of Madhya Pradesh, India, known for its historical and religious significance.
-
C.
Sarangpur
Sarangpur is a town in Gujarat, India, known as an important religious center for the Swaminarayan Sampradaya and a site of major Hindu temples and pilgrimage.
-
D.
Gondia
Gondia is a district in the Indian state of Maharashtra, known for its rice production and proximity to forests and wildlife reserves.
-
E.
Jalaun
Jalaun is a town in the Indian state of Uttar Pradesh known for its administrative role within the surrounding Jalaun district.
- 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_69e11e57483c8190b0887c4f8ff26446 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15ed4d4608190ba93bb54f15334a5 |
completed | April 29, 2026, 1:28 a.m. |
Created at: April 16, 2026, 8:51 p.m.