Triple
T28906114
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Best Amateur Series |
E733082
|
entity |
| Predicate | targetIndustrySegment |
P146868
|
FINISHED |
| Object | amateur pornography |
—
|
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: amateur pornography | Statement: [Best Amateur Series, targetIndustrySegment, amateur pornography]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: targetIndustrySegment Context triple: [Best Amateur Series, targetIndustrySegment, amateur pornography]
-
A.
ownerSector
Indicates the sector or industry category to which the owner of an entity belongs.
-
B.
acquisitionTargetIndustry
Indicates the industry or sector in which the company being acquired operates.
-
C.
targetIndustryDepicted
Indicates that an entity visually represents or portrays a specific industry as its primary subject or focus.
-
D.
targetsSector
Indicates that an entity is directed toward, focused on, or intended to affect a particular economic or industry sector.
-
E.
marketSegmentType
chosen
Indicates the specific category or segment of the market that an entity, product, or service is targeted toward or associated with.
- 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_69f05b096d208190958a57d2e4b5a93a |
completed | April 28, 2026, 7 a.m. |
| NER | Named-entity recognition | batch_69f7c777e924819081a6634f549fe552 |
completed | May 3, 2026, 10:08 p.m. |
| PD | Predicate disambiguation | batch_69f7c475c58c8190a883554231e88c88 |
completed | May 3, 2026, 9:56 p.m. |
Created at: April 28, 2026, 8:07 a.m.