Triple
T11956786
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Younger |
E284572
|
entity |
| Predicate | targetIndustryDepicted |
P102466
|
FINISHED |
| Object | publishing industry |
—
|
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: publishing industry | Statement: [Younger, targetIndustryDepicted, publishing industry]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: targetIndustryDepicted Context triple: [Younger, targetIndustryDepicted, publishing industry]
-
A.
containsIndustry
Indicates that one entity includes or encompasses a particular industry within its scope, structure, or operations.
-
B.
targetCompanyIndustry
Indicates that a company operates within or is associated with a specified industry sector.
-
C.
operatorIndustry
Indicates that an operator (such as a company or organization) is engaged in or associated with a particular industry sector.
-
D.
typicallyDepicts
Indicates that one entity is most commonly or characteristically portrayed or represented by the other in depictions or images.
-
E.
foundingIndustry
Indicates the industry or sector in which an entity was originally founded or began its primary operations.
- F. None of above. chosen
Provenance (4 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_69d6ab2db38c8190b1f0ed6663ef8ada |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d90366fda8819083168c93abad27d4 |
completed | April 10, 2026, 2:04 p.m. |
| PD | Predicate disambiguation | batch_69d8bb3e48e08190b2fee43af4f57323 |
completed | April 10, 2026, 8:56 a.m. |
| PDg | Predicate description generation | batch_69d8dd0ba0f88190b7d5e358c27ca184 |
completed | April 10, 2026, 11:20 a.m. |
Created at: April 8, 2026, 9:45 p.m.