Triple
T22804820
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michael Britten |
E564502
|
entity |
| Predicate | hasReality |
P29186
|
FINISHED |
| Object | Red reality |
—
|
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: Red reality | Statement: [Michael Britten, hasReality, Red reality]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasReality Context triple: [Michael Britten, hasReality, Red reality]
-
A.
realityStatus
chosen
Indicates the relationship between an entity and its state of existence or authenticity within a given context or world (e.g., real, fictional, hypothetical, simulated).
-
B.
hasRealityTVElement
Indicates that something includes characteristics, themes, or stylistic features commonly associated with reality television.
-
C.
hasRealForm
Indicates that an abstract, conceptual, or non-physical entity is associated with a concrete, physical manifestation or embodiment.
-
D.
levelOfReality
Indicates the degree or status of existence or authenticity that one entity has relative to another or within a given framework.
-
E.
hasRealModel
Indicates that an abstract, theoretical, or simplified entity is associated with a corresponding concrete or physically instantiated model in the real world.
- 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_69e245823f4c8190ade442cdcc2c224a |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17d5b37cc8190a41d8f304ba8d609 |
completed | April 29, 2026, 3:39 a.m. |
| PD | Predicate disambiguation | batch_69eed2cb30f481909566369f515f6eff |
completed | April 27, 2026, 3:06 a.m. |
Created at: April 17, 2026, 3:31 p.m.