Triple
T22599349
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saans |
E574769
|
entity |
| Predicate | lyricist |
P1360
|
FINISHED |
| Object | Gulzar |
—
|
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: Gulzar | Statement: [Saans, lyricist, Gulzar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gulzar Context triple: [Saans, lyricist, Gulzar]
-
A.
Gulzar
chosen
Gulzar is a renowned Indian poet, lyricist, and filmmaker celebrated for his evocative Urdu and Hindi writings and influential contributions to Indian cinema and music.
-
B.
Javed Akhtar
Javed Akhtar is a renowned Indian poet, lyricist, and screenwriter known for his influential work in Hindi cinema and outspoken advocacy of secularism and rational thought.
-
C.
Shailendra
Shailendra was a celebrated Indian poet and film lyricist, renowned for his evocative and timeless songs in classic Hindi cinema.
-
D.
Sahir Ludhianvi
Sahir Ludhianvi was a renowned Indian Urdu poet and Hindi film lyricist known for his progressive, socially conscious verse and iconic songs in classic Bollywood cinema.
-
E.
Naushad
Naushad was a legendary Indian film music director and composer renowned for his classical-based scores in Hindi cinema’s golden era.
- 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_69e245bc11308190b69d794d5d1e0bb6 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1626b5f5481909a104088d1c96720 |
completed | April 29, 2026, 1:44 a.m. |
Created at: April 17, 2026, 2:50 p.m.