Triple
T27283793
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Central Flores |
E688411
|
entity |
| Predicate | hasAcademicInterestFrom |
P90113
|
FINISHED |
| Object | linguists |
—
|
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: linguists | Statement: [Central Flores, hasAcademicInterestFrom, linguists]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAcademicInterestFrom Context triple: [Central Flores, hasAcademicInterestFrom, linguists]
-
A.
hasScientificInterestIn
chosen
Indicates that one entity holds a scientific curiosity, concern, or research focus directed toward another entity.
-
B.
regionOfAcademicInterest
Indicates that an entity has a particular academic field or subject area as its focus of interest or study.
-
C.
subjectInterest
Indicates that the subject has an interest in, or is concerned with, the object.
-
D.
hasSubjectOfStudy
Indicates that an entity (such as a person or organization) focuses on, researches, or specializes in a particular field or topic of study.
-
E.
usesResearchSubject
Indicates that one entity employs or utilizes another entity as a research subject in a study or investigation.
- 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_69ef355998e08190bdff849e8f33adce |
completed | April 27, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69f68805b4848190b75da14996d52a38 |
completed | May 2, 2026, 11:25 p.m. |
| PD | Predicate disambiguation | batch_69f68609c0b08190a8e1238a4d97c270 |
completed | May 2, 2026, 11:17 p.m. |
Created at: April 27, 2026, 11:09 a.m.