Triple
T37298139
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zoe Vachon |
E925860
|
entity |
| Predicate | creativeInterest |
P121014
|
FINISHED |
| Object | art |
—
|
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: art | Statement: [Zoe Vachon, creativeInterest, art]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: creativeInterest Context triple: [Zoe Vachon, creativeInterest, art]
-
A.
subjectInterest
Indicates that the subject has an interest in, or is concerned with, the object.
-
B.
primaryInterest
Indicates that one entity is the main or most significant focus of attention, concern, or engagement for another entity.
-
C.
artInterest
chosen
Indicates that one entity has an interest in, appreciation for, or engagement with art in relation to another entity or artistic subject.
-
D.
collectorInterest
Indicates that one entity has a special interest in acquiring, owning, or seeking out another entity as part of a collection.
-
E.
culturalInterest
Indicates a relationship where one entity has an interest in, appreciation for, or engagement with the culture, traditions, or cultural expressions 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_69f76eb0f86c819098dee07393e69ec3 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69ffe23081408190a121d901dbce1403 |
completed | May 10, 2026, 1:41 a.m. |
| PD | Predicate disambiguation | batch_69ffe18aed348190912a5996b2da728b |
completed | May 10, 2026, 1:38 a.m. |
Created at: May 3, 2026, 4:16 p.m.