Triple
T10398794
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Winston White |
E245088
|
entity |
| Predicate | hasTarContent |
P93708
|
FINISHED |
| Object | reduced compared to regular Winston |
—
|
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: reduced compared to regular Winston | Statement: [Winston White, hasTarContent, reduced compared to regular Winston]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTarContent Context triple: [Winston White, hasTarContent, reduced compared to regular Winston]
-
A.
hasContentFrom
Indicates that one entity’s content is derived from, includes, or is based on another entity.
-
B.
hasCollectionContent
Indicates that a collection includes or contains a specific item, element, or content as part of it.
-
C.
hasContentType
Indicates that an entity is associated with or classified by a specific type of content.
-
D.
hasTotalQuarkContent
Indicates that an entity (such as a particle or system) is associated with a specified total number or combination of quarks it contains.
-
E.
hasFiberContent
Indicates that one entity contains a specified amount or level of dietary fiber.
- 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_69d381b5116081908d85227bab6d3c0c |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4e9d1f2408190beaa8197641c66b4 |
completed | April 7, 2026, 11:26 a.m. |
| PD | Predicate disambiguation | batch_69d4dfb438c481908dff87c47de2f069 |
completed | April 7, 2026, 10:43 a.m. |
| PDg | Predicate description generation | batch_69d4e944fac4819093b0312aa0efd729 |
completed | April 7, 2026, 11:23 a.m. |
Created at: April 6, 2026, 12:07 p.m.