Triple
T3460231
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Planet Terror |
E73005
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Naveen Andrews |
E49514
|
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: Naveen Andrews | Statement: [Planet Terror, starring, Naveen Andrews]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Naveen Andrews Context triple: [Planet Terror, starring, Naveen Andrews]
-
A.
Naveen Andrews
chosen
Naveen Andrews is a British actor best known for his roles in the television series "Lost" and films such as "The English Patient."
-
B.
Karan Patel
Karan Patel is an Indian television actor best known for his role as Raman Bhalla in the popular Hindi TV series "Yeh Hai Mohabbatein."
-
C.
Neal Mohan
Neal Mohan is an Indian-American technology executive and digital advertising expert who serves as the CEO of YouTube.
-
D.
Amarjeet Sohi
Amarjeet Sohi is a Canadian politician who serves as the mayor of Edmonton and is a former federal cabinet minister.
-
E.
Andrij Parekh
Andrij Parekh is an American cinematographer and director known for his intimate, naturalistic visual style in independent films and television.
- 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_69ad85b224d481908ff8be51338d24ff |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adbae5ff848190880fa416a123bc4a |
completed | March 8, 2026, 6:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b373aaff688190b9f12a7042055a1c |
completed | March 13, 2026, 2:17 a.m. |
Created at: March 8, 2026, 3:17 p.m.