Triple
T172280
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Philip V of Spain |
E3500
|
entity |
| Predicate | causeOfWar |
P694
|
FINISHED |
| Object | accession to the Spanish throne |
—
|
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: accession to the Spanish throne | Statement: [Philip V of Spain, causeOfWar, accession to the Spanish throne]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: causeOfWar Context triple: [Philip V of Spain, causeOfWar, accession to the Spanish throne]
-
A.
causeOf
chosen
Indicates that one entity brings about, produces, or is responsible for the occurrence or existence of another entity or event.
-
B.
militaryConflict
Indicates a relationship where two or more parties are engaged in organized, armed hostilities or warfare against each other.
-
C.
causeOfDeath
Indicates the specific factor, event, or condition that directly resulted in an entity’s death.
-
D.
enemyDuringWar
Indicates that one entity is an enemy of another specifically in the context of a particular war or armed conflict.
-
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_69a25374990081909766d30c79a18e0e |
completed | Feb. 28, 2026, 2:31 a.m. |
| NER | Named-entity recognition | batch_69a25a3f9d188190aacf5791273e2c65 |
completed | Feb. 28, 2026, 3 a.m. |
| PD | Predicate disambiguation | batch_69a25667717c8190bac5108366e2178d |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:39 a.m.