Triple
T18448506
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Central City Police Department |
E450717
|
entity |
| Predicate | opposesFictionalGroup |
P17627
|
FINISHED |
| Object | Central City criminals |
—
|
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: Central City criminals | Statement: [Central City Police Department, opposesFictionalGroup, Central City criminals]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: opposesFictionalGroup Context triple: [Central City Police Department, opposesFictionalGroup, Central City criminals]
-
A.
opposesFictional
Indicates that one fictional entity is in opposition or conflict with another within a narrative or imagined context.
-
B.
hasAntagonistGroup
chosen
Indicates that an entity is opposed or challenged by a specific group acting as its antagonist.
-
C.
opposedByGroup
Indicates that an action, proposal, or entity is met with opposition or resistance from a particular group.
-
D.
associatedWithFictionalGroup
Indicates that an entity has a connection or affiliation with a fictional group, organization, or collective.
-
E.
opposingAlliance
Indicates that two entities belong to rival or mutually opposed alliances or factions.
- 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_69d8d38345688190b565eac2e4cd7935 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e52646949c81909664e864224675a6 |
completed | April 19, 2026, 7 p.m. |
| PD | Predicate disambiguation | batch_69e469c943a4819094c8fdc5971ad3a7 |
completed | April 19, 2026, 5:36 a.m. |
Created at: April 10, 2026, 11:30 a.m.