Triple
T25383635
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nefarious |
E631458
|
entity |
| Predicate | characterPortrayedBySeanPatrickFlanery |
P1507
|
FINISHED |
| Object | death row inmate claiming to be a demon |
—
|
LITERAL 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: death row inmate claiming to be a demon | Statement: [Nefarious, characterPortrayedBySeanPatrickFlanery, death row inmate claiming to be a demon]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characterPortrayedBySeanPatrickFlanery Context triple: [Nefarious, characterPortrayedBySeanPatrickFlanery, death row inmate claiming to be a demon]
-
A.
characterVoicedBy Seann William Scott
Indicates that a character is voiced by Seann William Scott.
-
B.
characterVoicedBy Denis Leary
Indicates that the character is voiced by Denis Leary.
-
C.
characterPlayedByRobertPatrick
Indicates that a given character is portrayed or acted by Robert Patrick.
-
D.
characterPortrayedIs
Indicates that one entity serves as the fictional or dramatic role that is depicted or played by another entity.
-
E.
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.
- 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_69e75a8c50788190aabaa9f96710fc43 |
completed | April 21, 2026, 11:07 a.m. |
| NER | Named-entity recognition | batch_69f65aa07c048190a5df30d53d8f0cf5 |
completed | May 2, 2026, 8:12 p.m. |
| PD | Predicate disambiguation | batch_69f659cc571c819097e51e531961d812 |
completed | May 2, 2026, 8:08 p.m. |
Created at: April 21, 2026, 1:46 p.m.