Triple
T22075979
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dilip Kumar |
E545521
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Andaz |
—
|
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: Andaz | Statement: [Dilip Kumar, notableWork, Andaz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Andaz Context triple: [Dilip Kumar, notableWork, Andaz]
-
A.
Andaz
Andaz is a luxury boutique hotel brand known for its contemporary design, locally inspired experiences, and personalized service.
-
B.
Andaz
chosen
Andaz is a classic 1949 Hindi romantic drama film, directed by Mehboob Khan and starring Raj Kapoor, Nargis, and Dilip Kumar, known for its love triangle and progressive themes.
-
C.
Rangbaaz
Rangbaaz is a Bangladeshi film that helped establish actor Razzak as a major star in the country’s cinema.
-
D.
Kabzaa
Kabzaa is a 1992 Hindi-language action crime film known for its underworld-centric storyline and ensemble cast, including Paresh Rawal.
-
E.
Andaandi
Andaandi is a Nubian language variety spoken primarily in the Dongola region of northern Sudan.
- 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.