Triple
T35154094
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Younger family |
E1015069
|
entity |
| Predicate | facesAntagonisticForce |
P4567
|
FINISHED |
| Object | Clybourne Park Improvement Association |
—
|
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: Clybourne Park Improvement Association | Statement: [Younger family, facesAntagonisticForce, Clybourne Park Improvement Association]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: facesAntagonisticForce Context triple: [Younger family, facesAntagonisticForce, Clybourne Park Improvement Association]
-
A.
facesAntagonistType
Indicates that an entity confronts or opposes an antagonist of a specified type.
-
B.
opposingForce
chosen
Indicates a relationship where one entity actively resists, counters, or works against the actions, goals, or influence of another entity.
-
C.
antagonistOf
Indicates a relationship where one entity actively opposes, conflicts with, or serves as an adversary to another.
-
D.
antagonistActionOf
Indicates that one entity performs an action in opposition or hostility toward another entity, acting as its antagonist.
-
E.
antagonisticArc
Indicates a relationship in which one entity consistently opposes, harms, or works against another over the course of a conflict or storyline.
- 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_69f76ddb3a708190b521ba2970b17178 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f78cf0cfdc81908da6f605f6988e8e |
completed | May 3, 2026, 5:59 p.m. |
| PD | Predicate disambiguation | batch_69f78b9106008190930b3b3675b737d6 |
completed | May 3, 2026, 5:53 p.m. |
Created at: May 3, 2026, 4:02 p.m.