Triple
T15158656
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gita Chandra |
E362148
|
entity |
| Predicate | relativeOf |
P367
|
FINISHED |
| Object | Haresh Chandra |
E360378
|
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: Haresh Chandra | Statement: [Gita Chandra, relativeOf, Haresh Chandra]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Haresh Chandra Context triple: [Gita Chandra, relativeOf, Haresh Chandra]
-
A.
Haresh Chandra
chosen
Haresh Chandra is an individual known primarily in this context as the child of Rani Chandra.
-
B.
Ashok Chandra
Ashok Chandra is a computer scientist known for his contributions to theoretical computer science and complexity theory.
-
C.
Nripendra Misra
Nripendra Misra is an Indian civil servant and former top bureaucrat who served as a key aide and principal advisor to Prime Minister Narendra Modi.
-
D.
Pradip Krishen
Pradip Krishen is an Indian filmmaker-turned-environmentalist and naturalist known for his documentaries and influential work on urban ecology and tree mapping in India.
-
E.
Akhilendra Mishra
Akhilendra Mishra is an Indian film and television actor known for his character roles in Hindi cinema and TV, including notable performances in movies like Lagaan and Sarfarosh.
- 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_69d85a087b7c81908baa94a53dac8d68 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0060dd71881908ecc4a4f52d438a5 |
completed | April 15, 2026, 9:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69feef64dbfc819098dac50500673ed4 |
completed | May 9, 2026, 8:25 a.m. |
Created at: April 10, 2026, 3:08 a.m.