Triple
T23609653
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Becky Williams |
E583000
|
entity |
| Predicate | emotionalAssociation |
P82444
|
FINISHED |
| Object | professional loyalty |
—
|
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: professional loyalty | Statement: [Becky Williams, emotionalAssociation, professional loyalty]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: emotionalAssociation Context triple: [Becky Williams, emotionalAssociation, professional loyalty]
-
A.
emotionAssociation
chosen
Indicates an emotional relationship or connection that one entity has toward another entity or concept.
-
B.
emotionSpectrumAffiliation
Indicates an entity’s association or alignment with a particular range or category of emotions along an emotional spectrum.
-
C.
emotionalFocusOf
Indicates that one entity is the primary target or center of another entity’s emotions or emotional attention.
-
D.
emotionalCounterpartOf
Indicates that one entity serves as the emotional equivalent, complement, or matching emotional role of another entity.
-
E.
emotionalTrait
Indicates that an entity possesses a particular emotional characteristic, disposition, or affective quality.
- 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_69e248faa2788190abb1581742daa6aa |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1b0f399cc8190a18d94b60fdca042 |
completed | April 29, 2026, 7:19 a.m. |
| PD | Predicate disambiguation | batch_69f118d0e0588190a86527a7747c5427 |
completed | April 28, 2026, 8:30 p.m. |
Created at: April 17, 2026, 6:44 p.m.