Triple
T35793161
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Blitz |
E1034743
|
entity |
| Predicate | targetOfAntagonist |
P196127
|
FINISHED |
| Object | police officers |
—
|
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: police officers | Statement: [Blitz, targetOfAntagonist, police officers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: targetOfAntagonist Context triple: [Blitz, targetOfAntagonist, police officers]
-
A.
targetOfAntagonists
chosen
Indicates that the referenced entity is the object or focus of hostile actions, opposition, or conflict initiated by antagonistic parties.
-
B.
antagonistOf
Indicates a relationship where one entity actively opposes, conflicts with, or serves as an adversary to another.
-
C.
leadAntagonistCharacter
Indicates that one character serves as the primary opposing or villainous force in relation to another entity in the narrative.
-
D.
missionOfAntagonist
Indicates the primary goal, plan, or objective that the antagonist is actively pursuing.
-
E.
antagonistBaseOf
Indicates that one entity serves as the primary base, headquarters, or stronghold from which an antagonist operates or exerts influence over 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_69f76e1575908190aaa306d843b41c14 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69fef2db323c8190821bda53f22a42be |
completed | May 9, 2026, 8:39 a.m. |
| PD | Predicate disambiguation | batch_69fef21d63c88190abf6a99b59b3c655 |
completed | May 9, 2026, 8:36 a.m. |
Created at: May 3, 2026, 4:06 p.m.