Triple
T7717057
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jyoti Bansal |
E174911
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Jyoti Bansal |
E174911
|
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: Jyoti Bansal | Statement: [Jyoti Bansal, name, Jyoti Bansal]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jyoti Bansal Context triple: [Jyoti Bansal, name, Jyoti Bansal]
-
A.
Jyoti Bansal
chosen
Jyoti Bansal is an Indian-American entrepreneur and technologist best known for founding the application performance management company AppDynamics, which was acquired by Cisco for billions of dollars.
-
B.
Jyoti Rathore
Jyoti Rathore is the daughter of Pratibha Patil, the former President of India.
-
C.
Sarita Khurana
Sarita Khurana is a filmmaker and producer known for her work on culturally focused, immigrant-centered stories in film and television.
-
D.
Rashmi Patel
Rashmi Patel is a personal name shared by multiple individuals, typically of Indian origin, and may refer to various professionals or public figures.
-
E.
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.
- 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_69c6995c463c8190a14458036249d419 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c702cd0ddc8190aa23d998f55d0bd6 |
completed | March 27, 2026, 10:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8c7beffc48190b39048b6afc1d644 |
completed | March 29, 2026, 6:33 a.m. |
Created at: March 27, 2026, 4:05 p.m.