Triple
T28519947
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | E Block |
E721731
|
entity |
| Predicate | filmActorAssociated |
P126404
|
FINISHED |
| Object | Tom Hanks |
—
|
NE NERFINISHED |
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 Hanks | Statement: [E Block, filmActorAssociated, Tom Hanks]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: filmActorAssociated Context triple: [E Block, filmActorAssociated, Tom Hanks]
-
A.
filmAssociatedWith
Indicates a general relationship or connection between a film and another entity, such as a person, organization, event, or work.
-
B.
associatedWithLeadActorOfFilm
chosen
Indicates a relationship where one entity is connected or linked in some relevant way to the lead actor of a specified film.
-
C.
bondActorInFilm
Indicates that the person is an actor who has portrayed the character James Bond in a film.
-
D.
directorAssociatedWith
Indicates a relationship where a director is professionally connected to, responsible for, or involved with a particular entity (such as a work, organization, or project).
-
E.
associatedWithProducerOfFilm
Indicates that one entity has an association or connection with the producer of a particular film.
- F. None of above.
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_69f01a5cbcc4819083fb4e723378713e |
completed | April 28, 2026, 2:24 a.m. |
| NER | Named-entity recognition | batch_69f64fa169e48190b061b3b3014a079d |
completed | May 2, 2026, 7:25 p.m. |
| PD | Predicate disambiguation | batch_69f64cb0d8008190912e1430cfaf92aa |
completed | May 2, 2026, 7:12 p.m. |
Created at: April 28, 2026, 3:20 a.m.