Triple
T2297959
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Richmond Valentine |
E51659
|
entity |
| Predicate | coverStory |
P7331
|
FINISHED |
| Object | global philanthropist fighting climate change |
—
|
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: global philanthropist fighting climate change | Statement: [Richmond Valentine, coverStory, global philanthropist fighting climate change]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: coverStory Context triple: [Richmond Valentine, coverStory, global philanthropist fighting climate change]
-
A.
cover
Indicates that one entity extends over, conceals, protects, or provides a surface or layer for another entity.
-
B.
mediaCovered
Indicates that one entity (such as a media outlet or source) has reported on, featured, or otherwise provided coverage of another entity or event.
-
C.
notableStory
chosen
Indicates that an entity is the subject or source of a story, account, or narrative that is considered notable or significant.
-
D.
featuredOn
Indicates that one entity is prominently presented, highlighted, or showcased on or within another entity (such as a platform, publication, or product).
-
E.
featuredIn
Indicates that one entity appears or is prominently included within another entity, such as a person, work, or item being showcased in a larger work, event, or context.
- 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_69a88b0a9f248190bcff941463d8f65a |
completed | March 4, 2026, 7:42 p.m. |
| NER | Named-entity recognition | batch_69abcd0e42248190ada33b84d75caa64 |
completed | March 7, 2026, 7 a.m. |
| PD | Predicate disambiguation | batch_69abc589295c819092989820c2b4e9d8 |
completed | March 7, 2026, 6:28 a.m. |
Created at: March 4, 2026, 7:49 p.m.