Triple
T7990889
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kanchrapara |
E186001
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Kalyani |
E184770
|
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: Kalyani | Statement: [Kanchrapara, locatedNear, Kalyani]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kalyani Context triple: [Kanchrapara, locatedNear, Kalyani]
-
A.
Kalyani
chosen
Kalyani is a planned town in the Nadia district of West Bengal, India, known for its educational institutions, industries, and organized urban layout.
-
B.
Bhagyanagar
Bhagyanagar is an old historical name for the Indian city now known as Hyderabad.
-
C.
Krishnanagar
Krishnanagar is a historic town in eastern India known for its cultural heritage, temples, and traditional clay artistry.
-
D.
Mahendranagar
Mahendranagar is a major city in far‑western Nepal, serving as an important commercial and administrative hub near the Indian border.
-
E.
Partapur
Partapur is a locality in Meerut district of Uttar Pradesh, India, known for its proximity to the Dr. Bhimrao Ambedkar Airstrip and its growing urban and institutional development.
- 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_69ca829c6c308190ab05b43d234c52b2 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3c6fc19c8190b98023e257c2f4f2 |
completed | March 31, 2026, 3:15 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cc63b96ed48190b752865ef3855e46 |
completed | April 1, 2026, 12:15 a.m. |
Created at: March 30, 2026, 5:16 p.m.