Triple
T29147836
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Guido in Risky Business |
E738819
|
entity |
| Predicate | entanglesActorCharacterPlayedBy |
P9616
|
FINISHED |
| Object | Tom Cruise |
E138735
|
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: Tom Cruise | Statement: [Guido in Risky Business, entanglesActorCharacterPlayedBy, Tom Cruise]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: entanglesActorCharacterPlayedBy Context triple: [Guido in Risky Business, entanglesActorCharacterPlayedBy, Tom Cruise]
-
A.
playedBy
chosen
Indicates that a role, character, or performance is portrayed or executed by a specific person or agent.
-
B.
involvedActor
Indicates that an entity participates as an actor or participant in the referenced event, activity, or situation.
-
C.
oftenPlayedBy
Indicates that one entity frequently performs, portrays, or executes another entity, such as a role, character, or piece of music.
-
D.
arePlayedBy
Indicates that one or more performers (such as actors or musicians) carry out, interpret, or execute the referenced roles, characters, or pieces.
-
E.
worksForCharacterPlayedBy
Indicates that one character is employed by, or works under, another character who is portrayed by a specific actor.
- F. None of above.
Provenance (4 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_69f07cb46f148190874eb8576a447567 |
completed | April 28, 2026, 9:24 a.m. |
| NER | Named-entity recognition | batch_69f662a29b3881909957a7e3b986653c |
completed | May 2, 2026, 8:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a25506118dc81909c776e94e1c880de |
completed | June 7, 2026, 11:05 a.m. |
| PD | Predicate disambiguation | batch_69f65c2376a08190be5215171e908e69 |
completed | May 2, 2026, 8:18 p.m. |
Created at: April 28, 2026, 11:40 a.m.