Triple
T36697367
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bullseye |
E906127
|
entity |
| Predicate | frequentAdversaryOf |
P11706
|
FINISHED |
| Object | Daredevil |
—
|
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: Daredevil | Statement: [Bullseye, frequentAdversaryOf, Daredevil]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: frequentAdversaryOf Context triple: [Bullseye, frequentAdversaryOf, Daredevil]
-
A.
commonAdversary
Indicates that two or more entities share the same opponent, rival, or threat.
-
B.
otherAdversary
Indicates that one entity is an adversary of another, distinct from any primary or previously identified adversary.
-
C.
notableAdversary
chosen
Indicates that one entity is recognized as a significant or prominent opponent or rival of another entity.
-
D.
laterEnemyOf
Indicates that one entity becomes an enemy of another at a later time, after not initially being in an antagonistic relationship.
-
E.
hasFriendEnemyRelationshipWith
Indicates a relationship where two entities are simultaneously connected as both friends and enemies, reflecting a mixed or ambivalent association between them.
- 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_69f76e7195c48190b5580c9cfb01e95f |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69f7c7eb20548190a946a7257993b2a8 |
completed | May 3, 2026, 10:10 p.m. |
| PD | Predicate disambiguation | batch_69f7c4796ebc819084a0dc08505e5f14 |
completed | May 3, 2026, 9:56 p.m. |
Created at: May 3, 2026, 4:12 p.m.