Triple
T2350624
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yvonne McGuinness |
E47438
|
entity |
| Predicate | hasWorkCharacteristic |
P274
|
FINISHED |
| Object | immersive |
—
|
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: immersive | Statement: [Yvonne McGuinness, hasWorkCharacteristic, immersive]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWorkCharacteristic Context triple: [Yvonne McGuinness, hasWorkCharacteristic, immersive]
-
A.
hasCharacteristic
chosen
Indicates that an entity possesses, exhibits, or is defined by a particular attribute, feature, or quality.
-
B.
hasWorkBy
Indicates that one entity (such as a collection, exhibition, or publication) includes or contains creative works produced by another entity (such as an artist, author, or creator).
-
C.
hasWorkingMode
Indicates that an entity operates under or supports a particular mode or configuration of functioning.
-
D.
hasKeyWork
Indicates that an entity possesses or is associated with a primary or central work (such as a main publication, artwork, or project) that is especially representative or important.
-
E.
hasWorkAsSubject
Indicates that an entity serves as the subject (creator or originator) of a particular work or creative output.
- 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_69a88a1b678c8190bce986922ba60ce0 |
completed | March 4, 2026, 7:38 p.m. |
| NER | Named-entity recognition | batch_69abcb802da08190980100444010f91e |
completed | March 7, 2026, 6:53 a.m. |
| PD | Predicate disambiguation | batch_69abc5981ce48190a3f7852d28276e11 |
completed | March 7, 2026, 6:28 a.m. |
Created at: March 4, 2026, 7:54 p.m.