Triple
T11486261
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Charlene Fleming |
E272286
|
entity |
| Predicate | supportsAgainst |
P62898
|
FINISHED |
| Object | Dicky Eklund’s influence |
—
|
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: Dicky Eklund’s influence | Statement: [Charlene Fleming, supportsAgainst, Dicky Eklund’s influence]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsAgainst Context triple: [Charlene Fleming, supportsAgainst, Dicky Eklund’s influence]
-
A.
supportAgainst
chosen
Indicates providing help, resources, or advocacy to oppose or resist a particular target, threat, or adversary.
-
B.
supportsUse
Indicates that one entity enables, allows, or is compatible with the use or operation of another entity.
-
C.
supportedAfter
Indicates that one entity provided support to another only after a specified event, time, or condition had occurred.
-
D.
supportedSide
Indicates that one entity backed, favored, or provided assistance to a particular side or party in a conflict, dispute, or competition.
-
E.
supportsValue
Indicates that one entity provides justification, evidence, or backing for the truth, relevance, or appropriateness of a particular value associated with 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_69d6aae1b09881909ce2ded3fa0c14fa |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d85a1fc9688190aacc2eed64229b79 |
completed | April 10, 2026, 2:02 a.m. |
| PD | Predicate disambiguation | batch_69d808736c5c8190899b5b3b2e797f65 |
completed | April 9, 2026, 8:13 p.m. |
Created at: April 8, 2026, 9:36 p.m.