Triple
T33742918
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Huevos de oro |
E864618
|
entity |
| Predicate | ageRatingCountry |
P149658
|
FINISHED |
| Object | Spain |
—
|
NE NERFINISHED |
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: Spain | Statement: [Huevos de oro, ageRatingCountry, Spain]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ageRatingCountry Context triple: [Huevos de oro, ageRatingCountry, Spain]
-
A.
ageRatingContext
Indicates the contextual basis or circumstances (such as region, system, or criteria) under which an age rating is assigned or interpreted.
-
B.
ageRatingSystem
Indicates the classification scheme or standard used to assign age-appropriateness ratings to content.
-
C.
filmRatingRegion
chosen
Indicates the region or country for which a film’s content rating or classification is applicable.
-
D.
filmRatingCanada
Indicates the film’s official content rating as assigned by Canadian film classification authorities.
-
E.
ratedFor
Indicates that an entity has been evaluated and assigned a suitability or quality level for a particular purpose, context, or audience.
- 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_69f3498b24b8819096a65009e521d0e1 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f6fb5c15408190915e27f023429d58 |
completed | May 3, 2026, 7:38 a.m. |
| PD | Predicate disambiguation | batch_69f6f96dd4c8819093d6a7bd046a9ad5 |
completed | May 3, 2026, 7:29 a.m. |
Created at: May 1, 2026, 1:44 a.m.