Triple
T28653774
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gbandi people |
E725272
|
entity |
| Predicate | civilWarExperience |
P61727
|
FINISHED |
| Object | affected by the Liberian civil wars |
—
|
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: affected by the Liberian civil wars | Statement: [Gbandi people, civilWarExperience, affected by the Liberian civil wars]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: civilWarExperience Context triple: [Gbandi people, civilWarExperience, affected by the Liberian civil wars]
-
A.
civilWarPeriod
Indicates a time span during which a civil war is occurring or in effect.
-
B.
conflictExperience
chosen
Indicates that an entity has undergone or been involved in a conflict, such as a dispute, struggle, or confrontation.
-
C.
civilWarTheater
Indicates a geographic or operational area where events of a civil war take place or are focused.
-
D.
hasCivilWarAssociation
Indicates a relationship in which an entity is connected or related to a civil war, such as through involvement, impact, or relevance.
-
E.
従軍紛争
Indicates participation in or involvement with a military conflict or 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_69f01d84f5f0819087ab5e6143b14ed7 |
completed | April 28, 2026, 2:37 a.m. |
| NER | Named-entity recognition | batch_69f65a6c900881908f18b61273d7bf8d |
completed | May 2, 2026, 8:11 p.m. |
| PD | Predicate disambiguation | batch_69f659ce58408190ba9e007b4810d4d0 |
completed | May 2, 2026, 8:08 p.m. |
Created at: April 28, 2026, 4:53 a.m.