Triple
T50764
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Triple Alliance (1668) |
E995
|
entity |
| Predicate | hasTerm |
P2920
|
FINISHED |
| Object | defensive mutual assistance |
—
|
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: defensive mutual assistance | Statement: [Triple Alliance (1668), hasTerm, defensive mutual assistance]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTerm Context triple: [Triple Alliance (1668), hasTerm, defensive mutual assistance]
-
A.
hasConcept
Indicates that an entity includes, embodies, or is associated with a particular concept.
-
B.
hasRepresentationIn
Indicates that one entity is represented, depicted, or encoded within another entity, such as a concept, object, or data structure having a corresponding representation in a specific medium or context.
-
C.
hasPart
Indicates that one entity is a component, segment, or constituent part of another entity.
-
D.
hasCondition
Indicates that an entity possesses, experiences, or is affected by a particular condition or state.
-
E.
hasDefinition
Indicates that one entity provides the meaning, explanation, or definition of another entity.
- 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_69a2480baefc81909951b14058479aa2 |
completed | Feb. 28, 2026, 1:42 a.m. |
| NER | Named-entity recognition | batch_69a24ba7016481909d595402712db6e2 |
completed | Feb. 28, 2026, 1:57 a.m. |
| PD | Predicate disambiguation | batch_69a24ac23f04819080cef9365ed990d4 |
completed | Feb. 28, 2026, 1:54 a.m. |
| PDg | Predicate description generation | batch_69a24ba5da048190a484963cb5a9bb2b |
completed | Feb. 28, 2026, 1:57 a.m. |
Created at: Feb. 28, 2026, 1:47 a.m.