Triple
T18736437
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Douaumont |
E458174
|
entity |
| Predicate | battlefieldStatus |
P133351
|
FINISHED |
| Object | partially preserved battlefield landscape |
—
|
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: partially preserved battlefield landscape | Statement: [Douaumont, battlefieldStatus, partially preserved battlefield landscape]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: battlefieldStatus Context triple: [Douaumont, battlefieldStatus, partially preserved battlefield landscape]
-
A.
battlefieldFunction
Indicates the role or purpose an entity serves within a combat or battlefield context, such as its tactical or operational function during warfare.
-
B.
battlefieldOf
Indicates that a location is the site where a particular battle or military engagement took place.
-
C.
statusDuringBattle
Indicates the condition or state an entity has while a specific battle or combat event is taking place.
-
D.
battlefieldSector
Indicates a specific area or zone of a battlefield in which a military unit, action, or event is located or occurs.
-
E.
opposingForcesStatus
Indicates the current state or condition of two or more forces that are in conflict or opposition to each other.
- 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_69d8d394dc308190b6725073f5db324c |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e57689fa508190ad821d361cba9edf |
completed | April 20, 2026, 12:42 a.m. |
| PD | Predicate disambiguation | batch_69e48d03766c8190a43f7681842f4f8d |
completed | April 19, 2026, 8:06 a.m. |
| PDg | Predicate description generation | batch_69e49a9bcc0c81908df3e513fd6762ff |
completed | April 19, 2026, 9:04 a.m. |
Created at: April 10, 2026, 11:51 a.m.