Triple
T411372
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ouvrage Schoenenbourg |
E9495
|
entity |
| Predicate | defensiveRole |
P13143
|
FINISHED |
| Object | artillery support |
—
|
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: artillery support | Statement: [Ouvrage Schoenenbourg, defensiveRole, artillery support]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: defensiveRole Context triple: [Ouvrage Schoenenbourg, defensiveRole, artillery support]
-
A.
defensiveStructure
Indicates a relationship where one entity functions as a structure built or used to protect, defend, or fortify another entity or area.
-
B.
defensivePlan
Indicates a relationship where an entity formulates or adopts a strategy specifically intended to protect against threats, attacks, or other adverse actions.
-
C.
defender
Indicates a relationship where one entity protects, guards, or supports another entity against threats, attacks, or criticism.
-
D.
defends
Indicates that one entity protects or supports another entity against attack, criticism, or harm.
-
E.
defenseResult
Indicates the outcome or consequence of a defensive action or strategy in response to an attack or threat.
- 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_69a2e80111fc8190961d5b7c6154123f |
completed | Feb. 28, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69a2ed31681c8190ac32334562fb17fd |
completed | Feb. 28, 2026, 1:27 p.m. |
| PD | Predicate disambiguation | batch_69a2e9737694819080fde9adcc1aa4d4 |
completed | Feb. 28, 2026, 1:11 p.m. |
| PDg | Predicate description generation | batch_69a2ed3032148190beb3a516e437f8f8 |
completed | Feb. 28, 2026, 1:27 p.m. |
Created at: Feb. 28, 2026, 1:09 p.m.