Triple
T1887442
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Avengers: Age of Ultron |
E39993
|
entity |
| Predicate | stars |
P1956
|
FINISHED |
| Object | Jeremy Renner |
E166838
|
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: Jeremy Renner | Statement: [Avengers: Age of Ultron, stars, Jeremy Renner]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jeremy Renner Context triple: [Avengers: Age of Ultron, stars, Jeremy Renner]
-
A.
Jeremy Renner
chosen
Jeremy Renner is an American actor and musician best known for his roles in films such as "The Hurt Locker" and as Hawkeye in the Marvel Cinematic Universe.
-
B.
Jason Clarke
Jason Clarke is an Australian actor known for his intense performances in films such as "Zero Dark Thirty," "Dawn of the Planet of the Apes," and "Chappaquiddick."
-
C.
Ben Foster
Ben Foster is an American actor known for his intense, often gritty performances in films such as "3:10 to Yuma," "Hell or High Water," and "The Messenger."
-
D.
Aaron Eckhart
Aaron Eckhart is an American actor best known for his roles in films such as "The Dark Knight," "Thank You for Smoking," and "Erin Brockovich."
-
E.
Josh Brolin
Josh Brolin is an American actor known for his versatile performances in films such as "No Country for Old Men," "W." and for portraying Thanos in the Marvel Cinematic Universe.
- 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_69a88633e4fc8190b7eb40463e048ec5 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb121a3cc81909c60ac65627142d1 |
completed | March 7, 2026, 5:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69addf63863881908efd8010db14b8a8 |
completed | March 8, 2026, 8:43 p.m. |
Created at: March 4, 2026, 7:34 p.m.