Triple
T32549450
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maya Pass |
E831934
|
entity |
| Predicate | battleTheatre |
P710
|
FINISHED |
| Object | Pyrenees campaign |
—
|
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: Pyrenees campaign | Statement: [Maya Pass, battleTheatre, Pyrenees campaign]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: battleTheatre Context triple: [Maya Pass, battleTheatre, Pyrenees campaign]
-
A.
battlefieldOf
Indicates that a location is the site where a particular battle or military engagement took place.
-
B.
militaryTheater
chosen
Indicates that an entity is a geographic or operational area where military operations or campaigns are conducted.
-
C.
battleDepicted
Indicates that a work or representation visually portrays a specific battle or combat event.
-
D.
battleWasPartOf
Indicates that a specific battle occurred as a component or phase within a larger military campaign, war, or conflict.
-
E.
warTheaterContext
Indicates the broader war or military campaign within which a specific battle, operation, or conflict event takes place.
- 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_69f34925fd08819084cfe4ec566cb704 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6c8159edc8190b1c87015e0c820e8 |
completed | May 3, 2026, 3:59 a.m. |
| PD | Predicate disambiguation | batch_69f6c3f42fbc8190a06eb1044c9e6094 |
completed | May 3, 2026, 3:41 a.m. |
Created at: May 1, 2026, 1:02 a.m.