Triple
T26702185
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Ottway |
E673186
|
entity |
| Predicate | primaryAntagonistsFaced |
P81119
|
FINISHED |
| Object | wolf pack |
—
|
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: wolf pack | Statement: [John Ottway, primaryAntagonistsFaced, wolf pack]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryAntagonistsFaced Context triple: [John Ottway, primaryAntagonistsFaced, wolf pack]
-
A.
primaryAntagonists
chosen
Indicates that the referenced entities serve as the main opposing or adversarial forces in relation to a specified subject or narrative.
-
B.
primaryAntagonistSpeciesFaced
Indicates the species that serves as the main opposing or enemy group confronted by a given entity.
-
C.
primaryAntagonistType
Indicates the role or category of the main opposing force or adversary that serves as the central source of conflict.
-
D.
hasAntagonisticProtagonist
Indicates that the work features a main character who opposes or undermines the typical heroic or moral expectations of a traditional protagonist.
-
E.
primaryEnemy
Indicates that one entity is the main or most significant adversary or opponent of another entity.
- 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_69eecda2b49c8190a6c481cfc4c07954 |
completed | April 27, 2026, 2:44 a.m. |
| NER | Named-entity recognition | batch_69fe8f74748c8190bd14a856c057f9f7 |
completed | May 9, 2026, 1:35 a.m. |
| PD | Predicate disambiguation | batch_69fe8e7ed8088190929e0df67aca4de9 |
completed | May 9, 2026, 1:31 a.m. |
Created at: April 27, 2026, 3:32 a.m.