Triple
T32554455
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stargirl (TV series) |
E832059
|
entity |
| Predicate | featuresAntagonistTeam |
P108467
|
FINISHED |
| Object | Injustice Society |
—
|
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: Injustice Society | Statement: [Stargirl (TV series), featuresAntagonistTeam, Injustice Society]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresAntagonistTeam Context triple: [Stargirl (TV series), featuresAntagonistTeam, Injustice Society]
-
A.
featuresAntagonistEntity
chosen
Indicates that the subject includes or involves an entity serving as an antagonist in the context of a narrative, interaction, or scenario.
-
B.
antagonisticTeam
Indicates a relationship where two teams are in active opposition or conflict with each other.
-
C.
featuresTeamUp
Indicates that two or more entities collaborate or join forces to act together as a team.
-
D.
hasAntagonistGroup
Indicates that an entity is opposed or challenged by a specific group acting as its antagonist.
-
E.
featuresTeams
Indicates that something prominently presents or includes specific teams as a central element or focus.
- 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_69f34926b9848190ace47d2dd0a0de7c |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_6a0119132e848190820a688d139fbf75 |
completed | May 10, 2026, 11:47 p.m. |
| PD | Predicate disambiguation | batch_6a01188dfdec8190b7f675264a281733 |
completed | May 10, 2026, 11:45 p.m. |
Created at: May 1, 2026, 1:02 a.m.