Triple
T3555620
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | C. R. Das |
E75211
|
entity |
| Predicate | child |
P120
|
FINISHED |
| Object | Kalyani |
unclear NED1
|
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: [C. R. Das, child, Kalyani]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kalyani Context triple: [C. R. Das, child, Kalyani]
-
A.
Kalyani
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.
Kalyan
Kalyan is a major railway junction and suburban city in the Mumbai Metropolitan Region, serving as a key transit hub for long-distance and local trains in Maharashtra, India.
-
E.
Benipatti
Benipatti is a town in the Madhubani district of the Indian state of Bihar, known for its rural setting and proximity to the region’s famed Mithila culture.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide. chosen
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_69ad85d45090819086f34fb85d850a1e |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc0569fbc81909b855b6990c1415b |
completed | March 8, 2026, 6:30 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b38bf40dac8190837053dd315303af |
completed | March 13, 2026, 4 a.m. |
Created at: March 8, 2026, 3:20 p.m.