Triple
T26310777
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Libre Intense |
E661813
|
entity |
| Predicate | isFlankerOf |
P160237
|
FINISHED |
| Object | Libre |
—
|
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: Libre | Statement: [Libre Intense, isFlankerOf, Libre]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isFlankerOf Context triple: [Libre Intense, isFlankerOf, Libre]
-
A.
isFlankerOf
chosen
Indicates that one entity occupies or performs the role of a flanker in relation to another entity, typically providing support or coverage from the side.
-
B.
hasFlanker
Indicates that an entity is positioned or assigned as a flanking support or protection alongside another entity.
-
C.
followsLeadershipOf
Indicates that one entity accepts and acts under the guidance, direction, or authority of another entity’s leadership.
-
D.
wasCompanionOf
Indicates that one entity accompanied or associated closely with another, typically as a partner, ally, or fellow participant over some period of time.
-
E.
governingRelation
Indicates a relationship in which one entity exercises authority, control, or regulatory power over another.
- 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_69ee812dacfc81908484aade9120fba9 |
completed | April 26, 2026, 9:18 p.m. |
| NER | Named-entity recognition | batch_69f60ee7e6348190951e6f9647f5555b |
completed | May 2, 2026, 2:49 p.m. |
| PD | Predicate disambiguation | batch_69f60b874cc88190a487230abb69efea |
completed | May 2, 2026, 2:34 p.m. |
Created at: April 26, 2026, 10:22 p.m.