Triple
T35544958
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fighting (2009 film) |
E1027183
|
entity |
| Predicate | Harvey BoardenPortrayedBy |
P1507
|
FINISHED |
| Object | Terrence Howard |
—
|
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: Terrence Howard | Statement: [Fighting (2009 film), Harvey BoardenPortrayedBy, Terrence Howard]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: Harvey BoardenPortrayedBy Context triple: [Fighting (2009 film), Harvey BoardenPortrayedBy, Terrence Howard]
-
A.
portrayedBy
chosen
Indicates that one entity serves as the actor or performer who represents or plays the role of another entity in a work or medium.
-
B.
supportingCharacterPortrayedBy
Indicates that a supporting (non-leading) character in a work is portrayed or acted by a specific performer.
-
C.
portrayedByInSpinOff
Indicates that an entity is portrayed by a particular actor specifically in a spin-off production related to the original work.
-
D.
portrayedBySpouseOf
Indicates that something is portrayed or depicted by the spouse of a given entity.
-
E.
colleaguePortrayedBy
Indicates that one colleague is depicted or represented by another person, typically in a work or professional context.
- 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_69f76e008ba08190927acd8e5e0344c8 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f79a54aa3c8190b2bb5d790b2d42d4 |
completed | May 3, 2026, 6:56 p.m. |
| PD | Predicate disambiguation | batch_69f7961970408190b669cc556e30a608 |
completed | May 3, 2026, 6:38 p.m. |
Created at: May 3, 2026, 4:04 p.m.