Triple
T11240812
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shammi Kapoor |
E266067
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Andaz |
E904733
|
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: Andaz | Statement: [Shammi Kapoor, notableWork, Andaz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Andaz Context triple: [Shammi Kapoor, notableWork, Andaz]
-
A.
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.
-
B.
Andaz
Andaz is a luxury boutique hotel brand known for its contemporary design, locally inspired experiences, and personalized service.
-
C.
Rangbaaz
Rangbaaz is a Bangladeshi film that helped establish actor Razzak as a major star in the country’s cinema.
-
D.
Andaandi
Andaandi is a Nubian language variety spoken primarily in the Dongola region of northern Sudan.
-
E.
Ghum
Ghum is a small hill station in West Bengal, India, known for its high-altitude railway station on the Darjeeling Himalayan Railway and its scenic views of the surrounding Himalayas.
- 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_69d6aac656d48190b275efaa7d6074ee |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e919eaf48190a1457851cfc56afb |
completed | April 9, 2026, 5:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e4ad79e4788190af39186f37600a64 |
completed | April 19, 2026, 10:24 a.m. |
Created at: April 8, 2026, 9:30 p.m.