Triple
T5737984
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lata Mangeshkar |
E126544
|
entity |
| Predicate | influenced |
P9
|
FINISHED |
| Object | Sunidhi Chauhan |
E141592
|
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: Sunidhi Chauhan | Statement: [Lata Mangeshkar, influenced, Sunidhi Chauhan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sunidhi Chauhan Context triple: [Lata Mangeshkar, influenced, Sunidhi Chauhan]
-
A.
Sunidhi Chauhan
chosen
Sunidhi Chauhan is a prominent Indian playback singer known for her powerful, versatile voice and numerous hit songs across Bollywood films.
-
B.
Shreya Ghoshal
Shreya Ghoshal is a renowned Indian playback singer celebrated for her versatile voice and extensive work across multiple Indian film industries.
-
C.
Janki Chatti
Janki Chatti is a small Himalayan settlement in Uttarakhand, India, that serves as the primary road-access point and base for pilgrims trekking to the Yamunotri temple.
-
D.
Alka Yagnik
Alka Yagnik is a renowned Indian playback singer celebrated for her melodious voice and numerous hit songs in Hindi cinema since the 1980s.
-
E.
Farah Naaz
Farah Naaz is an Indian film actress known for her prominent roles in Hindi cinema during the late 1980s and early 1990s.
- 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_69c0083082288190b7478cead6b5430a |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0255c8c308190821f968ec41c5078 |
completed | March 22, 2026, 5:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c0a16436588190943a0b81ea9429d9 |
completed | March 23, 2026, 2:11 a.m. |
Created at: March 22, 2026, 3:47 p.m.