Triple
T21454500
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nashik division |
E529305
|
entity |
| Predicate | containsCity |
P294
|
FINISHED |
| Object | Malegaon |
—
|
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: Malegaon | Statement: [Nashik division, containsCity, Malegaon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Malegaon Context triple: [Nashik division, containsCity, Malegaon]
-
A.
Malegaon
chosen
Malegaon is a major textile and powerloom town in Maharashtra, India, known for its large Muslim population and vibrant weaving industry.
-
B.
Baramati
Baramati is a town in the Pune district of Maharashtra, India, known as an agricultural and industrial hub with historical and political significance.
-
C.
Latur
Latur is a city in the Marathwada region of western India known for its agricultural economy and for being the epicenter of a devastating earthquake in 1993.
-
D.
Nanded
Nanded is a historic city in the Indian state of Maharashtra, known as an important Sikh pilgrimage center and a major urban hub in the Marathwada region.
-
E.
Sangli
Sangli is a city in the Indian state of Maharashtra known for its fertile agricultural surroundings and prominence in sugar and turmeric production.
- 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_69e0c457579481909db68053ed99750c |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69e9e9d612e081909d00ca59a3621cc9 |
completed | April 23, 2026, 9:43 a.m. |
Created at: April 16, 2026, 6:07 p.m.