Triple
T14792571
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fleury-devant-Douaumont |
E347691
|
entity |
| Predicate | battlefieldType |
P111081
|
FINISHED |
| Object | zone rouge (red zone) |
—
|
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: zone rouge (red zone) | Statement: [Fleury-devant-Douaumont, battlefieldType, zone rouge (red zone)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: battlefieldType Context triple: [Fleury-devant-Douaumont, battlefieldType, zone rouge (red zone)]
-
A.
battlegroundType
chosen
Indicates the specific kind or category of environment in which a battle or conflict takes place.
-
B.
battlefieldOf
Indicates that a location is the site where a particular battle or military engagement took place.
-
C.
battlefieldSector
Indicates a specific area or zone of a battlefield in which a military unit, action, or event is located or occurs.
-
D.
battlefieldFunction
Indicates the role or purpose an entity serves within a combat or battlefield context, such as its tactical or operational function during warfare.
-
E.
warfareType
Indicates the specific kind or category of warfare that characterizes a given conflict or military engagement.
- 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_69d822ea8b7c819097dfadf3d45545e6 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69decd5ec43c8190ad7a10a556519bb0 |
completed | April 14, 2026, 11:27 p.m. |
| PD | Predicate disambiguation | batch_69de8c090d1081909b5a9bf437499d6c |
completed | April 14, 2026, 6:48 p.m. |
Created at: April 10, 2026, 1:31 a.m.