Triple
T32065109
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Matthew Rolston |
E818854
|
entity |
| Predicate | hasDirectedCommercialFor |
P150664
|
FINISHED |
| Object | L'Oréal |
—
|
NE NERFINISHED |
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: L'Oréal | Statement: [Matthew Rolston, hasDirectedCommercialFor, L'Oréal]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDirectedCommercialFor Context triple: [Matthew Rolston, hasDirectedCommercialFor, L'Oréal]
-
A.
hasCommercialAppeal
Indicates that something possesses qualities likely to attract buyers or generate profitable market interest.
-
B.
appearedInCommercialFor
chosen
Indicates that one entity was featured or took part in a commercial advertisement promoting another entity.
-
C.
hasCommercialField
Indicates that one entity possesses or is associated with a commercial-related field, area, or domain in relation to another entity.
-
D.
commercialDirector
Indicates that one entity serves as the commercial director (responsible for business and commercial operations) of another entity.
-
E.
commercialFundingSource
Indicates that the entity receives financial support or backing from a commercial (for-profit) organization or source.
- 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_69f348fecc088190af1470afe5a969f0 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69fe68a4b67881909ca1d9f276f922e0 |
completed | May 8, 2026, 10:50 p.m. |
| PD | Predicate disambiguation | batch_69fe680234c88190b01f953987b74972 |
completed | May 8, 2026, 10:47 p.m. |
Created at: May 1, 2026, 12:22 a.m.