Triple
T3536228
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jennifer Aniston |
E74778
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Bruce Almighty |
E178788
|
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: Bruce Almighty | Statement: [Jennifer Aniston, notableWork, Bruce Almighty]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bruce Almighty Context triple: [Jennifer Aniston, notableWork, Bruce Almighty]
-
A.
Bruce Almighty
chosen
Bruce Almighty is a 2003 comedy film in which Jim Carrey plays a man temporarily granted God's powers, with Morgan Freeman portraying God.
-
B.
Austin Powers
Austin Powers is a comedic, exaggerated British spy character created and portrayed by Mike Myers, best known for parodying James Bond–style espionage in the Austin Powers film series.
-
C.
Dayman
Dayman is a fictional heroic persona from "It's Always Sunny in Philadelphia," featured in the show's satirical musical storyline.
-
D.
Don
The Don is a major river in southwestern Russia that flows from the Central Russian Upland to the Sea of Azov, historically serving as an important trade route and cultural boundary.
-
E.
Don
Don is a masculine given name, often a short form of Donald, used in English-speaking countries.
- 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_69ad85d1a3948190931fd1ea1f49717b |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adbcc7b92481908d2d99948780f4d0 |
completed | March 8, 2026, 6:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b38bd237e881909df210a42346b572 |
completed | March 13, 2026, 4 a.m. |
Created at: March 8, 2026, 3:20 p.m.