Triple
T27034332
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Save The Crew |
E681010
|
entity |
| Predicate | opposedActionType |
P107791
|
FINISHED |
| Object | relocation of Columbus Crew to Austin, Texas |
—
|
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: relocation of Columbus Crew to Austin, Texas | Statement: [Save The Crew, opposedActionType, relocation of Columbus Crew to Austin, Texas]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: opposedActionType Context triple: [Save The Crew, opposedActionType, relocation of Columbus Crew to Austin, Texas]
-
A.
opposedOperation
Indicates that one operation is in conflict with, counters, or works against another operation.
-
B.
opposedBy
Indicates that one entity actively resists, disagrees with, or works against the actions, views, or position of another entity.
-
C.
opposedApproach
chosen
Indicates that one entity actively disagrees with, resists, or works against the method, strategy, or course of action proposed or taken by another entity.
-
D.
opposesEffectOf
Indicates that one entity counteracts, reduces, or nullifies the effect produced by another entity.
-
E.
opposedOutcome
Indicates that one entity’s outcome is in conflict with, counters, or works against the outcome associated with 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_69eeeb5566f08190813daf896fa3da04 |
completed | April 27, 2026, 4:51 a.m. |
| NER | Named-entity recognition | batch_69f6978fe97081908fe568091ad9b159 |
completed | May 3, 2026, 12:32 a.m. |
| PD | Predicate disambiguation | batch_69f69661e6ec8190948251c7516a32ad |
completed | May 3, 2026, 12:27 a.m. |
Created at: April 27, 2026, 7:15 a.m.