Triple
T28411251
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Picentine War |
E719666
|
entity |
| Predicate | hasBelligerentType |
P174372
|
FINISHED |
| Object | city-state |
—
|
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: city-state | Statement: [Picentine War, hasBelligerentType, city-state]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBelligerentType Context triple: [Picentine War, hasBelligerentType, city-state]
-
A.
belligerentFor
Indicates a relationship in which one entity is engaged in hostile or aggressive behavior toward, or in conflict with, another entity.
-
B.
belligerentAgainst
Indicates a hostile or aggressive stance, conflict, or antagonistic behavior directed by one entity against another.
-
C.
allegedBelligerent
Indicates that one entity is claimed or accused of being a hostile or warring party in relation to another entity or conflict.
-
D.
belligerentControl
Indicates that one party exercises control, authority, or coercive influence over another in a hostile or conflict-oriented context.
-
E.
hasOpposingForceType
Indicates that one force is characterized as being of a type that opposes or counteracts another force.
- F. None of above. chosen
Provenance (4 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_69eff6f0f37c8190b37bc6fab08a9449 |
completed | April 27, 2026, 11:53 p.m. |
| NER | Named-entity recognition | batch_69f6c20f209081909fb9ac8f95069f04 |
completed | May 3, 2026, 3:33 a.m. |
| PD | Predicate disambiguation | batch_69f6bd2415fc81908c23c311aebce66f |
completed | May 3, 2026, 3:12 a.m. |
| PDg | Predicate description generation | batch_69f6c125695c81909704c67bef4ce5b2 |
completed | May 3, 2026, 3:29 a.m. |
Created at: April 28, 2026, 1:27 a.m.