Triple
T22075927
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shakeel Badayuni |
E545520
|
entity |
| Predicate | workedWith |
P398
|
FINISHED |
| Object | Naushad |
—
|
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: Naushad | Statement: [Shakeel Badayuni, workedWith, Naushad]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Naushad Context triple: [Shakeel Badayuni, workedWith, Naushad]
-
A.
Naushad
chosen
Naushad was a legendary Indian film music director and composer renowned for his classical-based scores in Hindi cinema’s golden era.
-
B.
Rajesh Roshan
Rajesh Roshan is an Indian film music composer known for his melodic scores in numerous Bollywood films since the 1970s.
-
C.
Aftab Iqbal
Aftab Iqbal was the son of the renowned philosopher-poet Allama Muhammad Iqbal and a Pakistani academic and literary figure in his own right.
-
D.
Talat Mahmood
Talat Mahmood was a renowned Indian playback singer and ghazal vocalist, celebrated for his velvety voice and soulful, romantic songs in mid-20th-century Hindi cinema.
-
E.
Rehman
Rehman is a surname shared by various individuals, including the late Norwegian-Pakistani comedian and writer Shabana Rehman.
- 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_69e11e3523488190badd54b5d580c00d |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f128b2bf60819082d38e671f160b0f |
completed | April 28, 2026, 9:37 p.m. |
Created at: April 16, 2026, 8:28 p.m.