Triple
T37592359
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cortex Island |
E935290
|
entity |
| Predicate | antagonisticLocationFor |
P167967
|
FINISHED |
| Object | Crash Bandicoot |
—
|
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: Crash Bandicoot | Statement: [Cortex Island, antagonisticLocationFor, Crash Bandicoot]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: antagonisticLocationFor Context triple: [Cortex Island, antagonisticLocationFor, Crash Bandicoot]
-
A.
antagonistLocationFor
chosen
Indicates that a location serves as the primary place where an antagonist operates, resides, or exerts influence in relation to a given context or entity.
-
B.
opposingLocation
Indicates that two entities are located directly opposite each other, typically across a defined reference such as a street, corridor, or boundary.
-
C.
antagonistNearby
Indicates that an opposing or hostile entity is located in close physical proximity to the reference entity.
-
D.
antagonisticInteractionWith
Indicates a hostile or oppositional interaction in which one entity acts against, harms, or obstructs another.
-
E.
antagonistOf
Indicates a relationship where one entity actively opposes, conflicts with, or serves as an adversary to another.
- 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_69f76ecf39c081909baffe597bb55273 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fbacaf54648190811ea33b34907e8e |
completed | May 6, 2026, 9:03 p.m. |
| PD | Predicate disambiguation | batch_69fba883f770819091059c6f6c6af9f7 |
completed | May 6, 2026, 8:45 p.m. |
Created at: May 3, 2026, 4:18 p.m.