Triple
T6154714
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Toledo War |
E137289
|
entity |
| Predicate | armedConflictLevel |
P69493
|
FINISHED |
| Object | limited skirmishes only |
—
|
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: limited skirmishes only | Statement: [Toledo War, armedConflictLevel, limited skirmishes only]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: armedConflictLevel Context triple: [Toledo War, armedConflictLevel, limited skirmishes only]
-
A.
militaryConflict
Indicates a relationship where two or more parties are engaged in organized, armed hostilities or warfare against each other.
-
B.
regionOfConflict
Indicates that a specified region is the location where a particular conflict or dispute takes place.
-
C.
politicalConflict
Indicates a relationship where entities are engaged in opposing political positions, struggles, or disputes, often involving competition for power, influence, or policy outcomes.
-
D.
militaryConflictView
Indicates a perspective, interpretation, or representation of a specific military conflict or battle.
-
E.
conflictBelligerent
Indicates that an entity is a participating belligerent (e.g., a country, group, or force) in a specific conflict.
- 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_69c008a45d008190832a9e19f5d63406 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c05d01ddb0819085b5f5338b86a25d |
completed | March 22, 2026, 9:20 p.m. |
| PD | Predicate disambiguation | batch_69c055f39e0881909ae56444b1b48929 |
completed | March 22, 2026, 8:49 p.m. |
| PDg | Predicate description generation | batch_69c056c87340819088003f427706ebf8 |
completed | March 22, 2026, 8:53 p.m. |
Created at: March 22, 2026, 4:17 p.m.