Triple
T28653432
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LURD |
E725261
|
entity |
| Predicate | influencedOutcomeOf |
P132927
|
FINISHED |
| Object | resignation and exile of Charles Taylor in 2003 |
—
|
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: resignation and exile of Charles Taylor in 2003 | Statement: [LURD, influencedOutcomeOf, resignation and exile of Charles Taylor in 2003]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: influencedOutcomeOf Context triple: [LURD, influencedOutcomeOf, resignation and exile of Charles Taylor in 2003]
-
A.
influencedIn
Indicates that one entity had an effect on or shaped another entity within a specific context, domain, or setting.
-
B.
influenced
Indicates that one entity has affected, shaped, or altered another entity’s state, behavior, or characteristics.
-
C.
consequenceOfInfluence
chosen
Indicates that one event, state, or condition occurs as a result of the influence or impact exerted by another.
-
D.
influenceOf
Indicates that one entity affects, shapes, or alters the state, behavior, or properties of another entity.
-
E.
hadInfluenceOn
Indicates that one entity affected, shaped, or contributed to the development, behavior, or characteristics of another entity.
- 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_69f6f8565134819096aac0175f924a9f |
completed | May 3, 2026, 7:25 a.m. |
| PD | Predicate disambiguation | batch_69f6f65fd1d08190b88e5e68ba268500 |
completed | May 3, 2026, 7:16 a.m. |
Created at: April 28, 2026, 4:53 a.m.