Triple
T22442052
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dev Anand |
E554776
|
entity |
| Predicate | stageName |
P7872
|
FINISHED |
| Object | Dev Anand |
—
|
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: Dev Anand | Statement: [Dev Anand, stageName, Dev Anand]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dev Anand Context triple: [Dev Anand, stageName, Dev Anand]
-
A.
Dev Anand
chosen
Dev Anand was a legendary Indian film actor, director, and producer, celebrated as one of Hindi cinema’s most charismatic and enduring stars.
-
B.
Dharmendra
Dharmendra is a legendary Indian film actor, often called the "He-Man" of Bollywood, known for his prolific work in Hindi cinema since the 1960s.
-
C.
Shashi Kapoor
Shashi Kapoor was a prominent Indian film actor and producer, known for his work in Hindi cinema and international films, and as a member of the influential Kapoor family.
-
D.
Dilip Kumar
Dilip Kumar was a legendary Indian film actor, celebrated as the "Tragedy King" of Hindi cinema and renowned for his intense, nuanced performances in classic Bollywood films.
-
E.
Utpal Dutt
Utpal Dutt was a renowned Indian actor, director, and playwright, celebrated for his powerful performances in both serious cinema and popular comedies, as well as his influential work in Bengali theatre.
- 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_69e11e5010e48190ae1e9c9db9697637 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15ae2f7608190b1c1e8bd12ca2162 |
completed | April 29, 2026, 1:12 a.m. |
Created at: April 16, 2026, 8:47 p.m.