Triple
T27864238
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Royal Warrant of 1917 |
E704312
|
entity |
| Predicate | warTime |
P21863
|
FINISHED |
| Object | World War I |
—
|
NE NERFINISHED |
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: World War I | Statement: [Royal Warrant of 1917, warTime, World War I]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: warTime Context triple: [Royal Warrant of 1917, warTime, World War I]
-
A.
warName
Indicates the specific name or title assigned to a particular war or armed conflict.
-
B.
warTimeEvent
Indicates an event that occurs during a period of war or armed conflict, typically as part of or directly influenced by that conflict.
-
C.
warPeriod
chosen
Indicates a time span during which a state of war or armed conflict is ongoing between parties.
-
D.
warTimeOnly
Indicates that the relationship or action occurs exclusively during periods of war or active armed conflict.
-
E.
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.
- 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_69ef840f12408190b539d00d79658abf |
completed | April 27, 2026, 3:43 p.m. |
| NER | Named-entity recognition | batch_69f63946708881908e441f37c8bd6fee |
completed | May 2, 2026, 5:49 p.m. |
| PD | Predicate disambiguation | batch_69f6318ae6f08190b3f85f9201046a15 |
completed | May 2, 2026, 5:16 p.m. |
Created at: April 27, 2026, 6:19 p.m.