Triple
T10676824
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Being There |
E251641
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Jack Warden |
E180195
|
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: Jack Warden | Statement: [Being There, starring, Jack Warden]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jack Warden Context triple: [Being There, starring, Jack Warden]
-
A.
Jack Warden
chosen
Jack Warden was an American character actor known for his prolific film and television career, including notable roles in classics like "12 Angry Men," "Heaven Can Wait," and "Shampoo."
-
B.
George Sowards
George Sowards is an actor known for his role in the film "Shotgun."
-
C.
Robert Joy
Robert Joy is a Canadian actor best known for his character roles in film and television, including his work on the crime drama series CSI: NY.
-
D.
Leo Willis
Leo Willis was an American character actor active during the silent and early sound film eras, often appearing in comedies alongside stars like Harold Lloyd.
-
E.
Warren Foster
Warren Foster was an American animation writer best known for his influential work on classic Warner Bros. cartoons, including many featuring characters like Foghorn Leghorn.
- 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_69d6aa5b0d2881909584b20efc5877f0 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d6fb9563908190a69cf4bd2c24fd2f |
completed | April 9, 2026, 1:06 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69de225f57948190aaf2954bce91f752 |
completed | April 14, 2026, 11:17 a.m. |
Created at: April 8, 2026, 9:09 p.m.