Triple
T38242671
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Martin Brewer |
E1013808
|
entity |
| Predicate | familyFriendlyShow |
P17278
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Martin Brewer, familyFriendlyShow, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: familyFriendlyShow Context triple: [Martin Brewer, familyFriendlyShow, true]
-
A.
TVShare
Indicates a relationship where one entity shares access to or usage of a television (or TV-related content/service) with another entity.
-
B.
builtForFamily
Indicates that something is designed or constructed specifically to accommodate the needs, activities, or preferences of a family.
-
C.
isFamilyFriendly
chosen
Indicates that something is suitable for all ages and does not contain content inappropriate for children or sensitive audiences.
-
D.
hasKidFriendlyFeatures
Indicates that something possesses characteristics, amenities, or design elements that are suitable and appealing for children.
-
E.
ageRatingContext
Indicates the contextual basis or circumstances (such as region, system, or criteria) under which an age rating is assigned or interpreted.
- 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_69f76dd7e89c8190b7866bc85aea521b |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fd4d1854988190be093b103a681798 |
completed | May 8, 2026, 2:40 a.m. |
| PD | Predicate disambiguation | batch_69fd4c8d1a188190897c24527337814a |
completed | May 8, 2026, 2:38 a.m. |
Created at: May 3, 2026, 4:30 p.m.