Triple
T22273872
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sholay |
E550550
|
entity |
| Predicate | castMember |
P1668
|
FINISHED |
| Object | Asrani |
—
|
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: Asrani | Statement: [Sholay, castMember, Asrani]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Asrani Context triple: [Sholay, castMember, Asrani]
-
A.
Asrani
chosen
Asrani is an Indian actor and comedian best known for his prolific work in Hindi cinema, particularly in classic Bollywood films from the 1970s and 1980s.
-
B.
Arnish
Arnish is a small village located on the Isle of Raasay in the Inner Hebrides of Scotland.
-
C.
Ganga Asnan
Ganga Asnan is a Hindu religious festival observed by Indo-Mauritians that centers on ritual bathing in sacred waters to honor the river goddess Ganga and seek spiritual purification.
-
D.
Aheri
Aheri is a legislative assembly constituency located in the Gadchiroli district of Maharashtra, India.
-
E.
Asshai
Asshai is a mysterious, far-eastern city in the world of "A Song of Ice and Fire," famed for its pervasive darkness, sorcery, and ominous reputation among travelers and loremasters.
- 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_69e11e43d8208190aff4f9cf7f2c2a8a |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f14ea547e4819098baf88f3c605242 |
completed | April 29, 2026, 12:19 a.m. |
Created at: April 16, 2026, 8:40 p.m.