Triple
T3218406
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cruz Beckham |
E67450
|
entity |
| Predicate | hasPublicImageAs |
P13872
|
FINISHED |
| Object | celebrity child |
—
|
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: celebrity child | Statement: [Cruz Beckham, hasPublicImageAs, celebrity child]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPublicImageAs Context triple: [Cruz Beckham, hasPublicImageAs, celebrity child]
-
A.
hasPublic
Indicates that an entity is accessible or visible to the general public rather than being private or restricted.
-
B.
publicImage
chosen
Indicates how an entity is perceived or represented by the general public or broader audience.
-
C.
hasMainImageSource
Indicates that an entity is associated with a primary image file or URL that serves as its main visual representation.
-
D.
hasPhotograph
Indicates that one entity possesses, includes, or is associated with a photograph depicting or representing another entity.
-
E.
hasKeyImage
Indicates that one entity is designated as the primary or representative image 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_69ad858b8adc8190ad989712c87a476b |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69adab0c48b481909d1bd9dc41dfa8c2 |
completed | March 8, 2026, 4:59 p.m. |
| PD | Predicate disambiguation | batch_69ad9e0bb6c48190a0659c67d40ee37c |
completed | March 8, 2026, 4:04 p.m. |
Created at: March 8, 2026, 3:08 p.m.