Triple
T20083963
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thapar |
E500073
|
entity |
| Predicate | usedBy |
P260
|
FINISHED |
| Object | Neha Thapar |
—
|
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: Neha Thapar | Statement: [Thapar, usedBy, Neha Thapar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Neha Thapar Context triple: [Thapar, usedBy, Neha Thapar]
-
A.
Rohini Thapar
chosen
Rohini Thapar is an individual associated with the Thapar name, likely as a member of or contributor to the prominent Thapar family or its enterprises.
-
B.
Sharan Narang
Sharan Narang is a machine learning researcher known for his work on large-scale natural language processing models, including contributions to the development of the T5 transformer architecture.
-
C.
Deepa Bhatia
Deepa Bhatia is an Indian film editor known for her acclaimed work on several Hindi films, including the critically celebrated drama "Taare Zameen Par."
-
D.
Sheila Dikshit
Sheila Dikshit was a prominent Indian National Congress politician who served as the long-time Chief Minister of Delhi, overseeing significant urban development and governance reforms in the capital.
-
E.
Persis Khambatta
Persis Khambatta was an Indian model and actress best known internationally for her role as Lieutenant Ilia in "Star Trek: The Motion Picture."
- 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_69da627770948190997f486f9a2e370f |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e6655a2d2c81908a6b8fd2f209a825 |
completed | April 20, 2026, 5:41 p.m. |
Created at: April 11, 2026, 3:41 p.m.