Triple
T6954157
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kaylon 1 |
E161198
|
entity |
| Predicate | originOfConflict |
P61068
|
FINISHED |
| Object | Kaylon–Planetary Union war attempt |
—
|
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: Kaylon–Planetary Union war attempt | Statement: [Kaylon 1, originOfConflict, Kaylon–Planetary Union war attempt]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: originOfConflict Context triple: [Kaylon 1, originOfConflict, Kaylon–Planetary Union war attempt]
-
A.
hasCauseOfConflict
chosen
Indicates a relationship where one entity is the source or reason for a conflict involving another entity.
-
B.
causeOfPoliticalConflict
Indicates that one entity is the source or reason for a political conflict involving another entity.
-
C.
conflictCountry
Indicates that there is an armed conflict or war involving the referenced country as a participant.
-
D.
settingOfConflict
Indicates the location or context in which a conflict between entities takes place.
-
E.
conflictBelligerent
Indicates that an entity is a participating belligerent (e.g., a country, group, or force) in a specific conflict.
- 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_69c68852a9a0819097797e31d492e273 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6dacca12481908942ba793a104cc3 |
completed | March 27, 2026, 7:30 p.m. |
| PD | Predicate disambiguation | batch_69c6d7bf0a7c8190b5ed4aca22ba9b97 |
completed | March 27, 2026, 7:17 p.m. |
Created at: March 27, 2026, 2:29 p.m.