Triple
T31102096
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Justice League film series |
E792700
|
entity |
| Predicate | primaryAntagonistInContinuity |
P81119
|
FINISHED |
| Object | Steppenwolf |
E199977
|
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: Steppenwolf | Statement: [Justice League film series, primaryAntagonistInContinuity, Steppenwolf]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryAntagonistInContinuity Context triple: [Justice League film series, primaryAntagonistInContinuity, Steppenwolf]
-
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.
primaryAntagonistType
Indicates the role or category of the main opposing force or adversary that serves as the central source of conflict.
-
C.
fullyIntroducedAsAntagonistIn
Indicates that an entity is completely and explicitly presented in a work as an antagonist within the specified context or narrative.
-
D.
antagonistAlterEgoOf
Indicates that one entity serves as the primary opposing force or enemy of another entity’s alternate identity or secret persona.
-
E.
mainAntagonistPortrayedBy
Indicates that the person is the primary actor who plays the main antagonist character in a work.
- 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_69f224cf157c81909e2d2bd88c9282c3 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_6a037c876524819098545e6037d3107d |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a2947135cec8190897ffaea6cff3a6b |
completed | June 10, 2026, 11:14 a.m. |
| PD | Predicate disambiguation | batch_6a0379e5174c8190a0bdde7e381b7624 |
completed | May 12, 2026, 7:05 p.m. |
Created at: April 29, 2026, 9:03 p.m.