Triple
T243676
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | French Wars of Religion |
E4988
|
entity |
| Predicate | numberOfWars |
P9747
|
FINISHED |
| Object | eight |
—
|
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: eight | Statement: [French Wars of Religion, numberOfWars, eight]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfWars Context triple: [French Wars of Religion, numberOfWars, eight]
-
A.
numberOfParticipatingNations
Indicates the total count of nations that take part in a specified event, activity, or context.
-
B.
majorWar
Indicates a large-scale, intense armed conflict between major powers or involving substantial military forces and widespread impact.
-
C.
worldWar
Indicates a large-scale armed conflict involving multiple nations across different regions of the world, typically encompassing numerous battles, alliances, and theaters of war.
-
D.
militaryConflict
Indicates a relationship where two or more parties are engaged in organized, armed hostilities or warfare against each other.
-
E.
enemyDuringWar
Indicates that one entity is an enemy of another specifically in the context of a particular war or armed conflict.
- 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_69a257c3d0708190b0871c4269d273e6 |
completed | Feb. 28, 2026, 2:49 a.m. |
| NER | Named-entity recognition | batch_69a25dcd2b208190855d5d8d70a3acfc |
completed | Feb. 28, 2026, 3:15 a.m. |
| PD | Predicate disambiguation | batch_69a25b62839c8190824064fe5da6a92a |
completed | Feb. 28, 2026, 3:05 a.m. |
| PDg | Predicate description generation | batch_69a25dcba5148190ab80fd14c7cf4bb4 |
completed | Feb. 28, 2026, 3:15 a.m. |
Created at: Feb. 28, 2026, 2:53 a.m.