Triple
T37694420
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alpine Div. |
E938888
|
entity |
| Predicate | hasTypicalSubType |
P154457
|
FINISHED |
| Object | mountain infantry division |
—
|
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: mountain infantry division | Statement: [Alpine Div., hasTypicalSubType, mountain infantry division]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypicalSubType Context triple: [Alpine Div., hasTypicalSubType, mountain infantry division]
-
A.
hasStructuralSubtype
chosen
Indicates that one structure is a more specific, subordinate form or subtype of another structure within a structural hierarchy.
-
B.
hasTypicalInstance
Indicates that a class or category is exemplified by a specific, representative instance that typifies its general characteristics.
-
C.
hasTypicalUsageType
Indicates that something is associated with a standard or commonly expected way in which it is used.
-
D.
hasSubstitutionsType
Indicates that an entity is associated with a specific kind or category of substitutions applied to it or occurring within it.
-
E.
hasTypicalSubject
Indicates that something is commonly or characteristically used as the subject (agent or topic) of a given relation or action.
- 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_69f76eda6ae48190b3111071eeacc038 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fff59a00a881909b35b799654b3c45 |
completed | May 10, 2026, 3:03 a.m. |
| PD | Predicate disambiguation | batch_69fff4d0a2e081909c972189b33d0128 |
completed | May 10, 2026, 3 a.m. |
Created at: May 3, 2026, 4:18 p.m.