Triple
T4709956
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Into the Blue |
E104483
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Josh Brolin |
E69966
|
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: Josh Brolin | Statement: [Into the Blue, starring, Josh Brolin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Josh Brolin Context triple: [Into the Blue, starring, Josh Brolin]
-
A.
Josh Brolin
chosen
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.
-
B.
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."
-
C.
Anthony Redman
Anthony Redman is a film editor best known for his work on the 1990 crime drama "King of New York."
-
D.
Joel David Moore
Joel David Moore is an American actor and director best known for his roles in films like "Avatar" and the TV series "Bones."
-
E.
Eric Bana
Eric Bana is an Australian actor known for his versatile performances in films such as "Hulk," "Munich," and "Troy."
- 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_69bd43eac3c08190af7e4020c6c3704c |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd63ee712c81908da60aa0df58efe0 |
completed | March 20, 2026, 3:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be1078784c81908e9a3fd0b168cadc |
completed | March 21, 2026, 3:28 a.m. |
Created at: March 20, 2026, 1:17 p.m.