Triple
T20237612
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mamta |
E498191
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Dharmendra |
—
|
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: Dharmendra | Statement: [Mamta, starring, Dharmendra]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dharmendra Context triple: [Mamta, starring, Dharmendra]
-
A.
Dharmendra
chosen
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.
-
B.
Dev Anand
Dev Anand was a legendary Indian film actor, director, and producer, celebrated as one of Hindi cinema’s most charismatic and enduring stars.
-
C.
Sanjeev Kumar
Sanjeev Kumar was a highly acclaimed Indian film actor known for his versatile performances in both mainstream and parallel cinema during the 1960s and 1970s.
-
D.
Tarun Dutt
Tarun Dutt was the son of legendary Indian filmmaker and actor Guru Dutt, known primarily for his connection to this iconic figure in Indian cinema.
-
E.
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.
- 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_69da6274c58c81909c646eabed6f4f30 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e6716b4c148190bf663b8a747fbfa5 |
completed | April 20, 2026, 6:33 p.m. |
Created at: April 11, 2026, 11:40 p.m.