Triple
T16503938
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sam Craig |
E400871
|
entity |
| Predicate | hasOnScreenProfessionContext |
P77347
|
FINISHED |
| Object | sports journalism |
—
|
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: sports journalism | Statement: [Sam Craig, hasOnScreenProfessionContext, sports journalism]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOnScreenProfessionContext Context triple: [Sam Craig, hasOnScreenProfessionContext, sports journalism]
-
A.
subjectHasOccupationContext
chosen
Indicates that a subject’s occupation is specified or interpreted within a particular contextual framework (such as time, place, or situation).
-
B.
hasNotableProfessionField
Indicates that an entity’s notable profession or occupation belongs to a particular professional field or domain.
-
C.
hasProfessionalSection
Indicates that an entity includes or is associated with a designated professional section, division, or category within its structure or content.
-
D.
hasProfessionTrait
Indicates that an entity possesses a particular characteristic, quality, or attribute specifically related to their profession or occupational role.
-
E.
includesProfession
Indicates that one entity’s set of attributes, roles, or members contains a specific profession as part of it.
- 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_69d88381f6148190819958a038be990e |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e32e5100e48190a623d6ee2fefb87e |
completed | April 18, 2026, 7:10 a.m. |
| PD | Predicate disambiguation | batch_69e296902d6c8190884ddb612b8c5b36 |
completed | April 17, 2026, 8:22 p.m. |
Created at: April 10, 2026, 5:14 a.m.