Triple
T22727121
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Luminaries (TV series) |
E562024
|
entity |
| Predicate | stars |
P1956
|
FINISHED |
| Object | Himesh Patel |
—
|
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: Himesh Patel | Statement: [The Luminaries (TV series), stars, Himesh Patel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Himesh Patel Context triple: [The Luminaries (TV series), stars, Himesh Patel]
-
A.
Himesh Patel
chosen
Himesh Patel is a British actor best known for his breakout lead role in the film "Yesterday" and supporting performances in major productions like "Tenet" and the series "Station Eleven."
-
B.
Sacha Dhawan
Sacha Dhawan is a British actor known for his versatile television and film roles, including his acclaimed portrayal of the Master in the long-running sci-fi series Doctor Who.
-
C.
Aditya Patel
Aditya Patel is a character from the Indian political drama film "Hu Tu Tu."
-
D.
Avan Jogia
Avan Jogia is a Canadian actor best known for his breakout role on the Nickelodeon series "Victorious" and subsequent work in film and television.
-
E.
John Abraham
John Abraham is an Indian film actor and producer known for his work in Hindi cinema, particularly in action and thriller 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_69e24550859c81908727d91efc3a81b4 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f1792a2ee48190bfbdde1a72adfd25 |
completed | April 29, 2026, 3:21 a.m. |
Created at: April 17, 2026, 3:20 p.m.