Triple
T14273240
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pelforth–Sauvage–Lejeune |
E353845
|
entity |
| Predicate | mainSponsorIndustry |
P33295
|
FINISHED |
| Object | brewery |
—
|
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: brewery | Statement: [Pelforth–Sauvage–Lejeune, mainSponsorIndustry, brewery]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainSponsorIndustry Context triple: [Pelforth–Sauvage–Lejeune, mainSponsorIndustry, brewery]
-
A.
sponsorshipIndustry
Indicates a relationship where one entity sponsors another specifically within a given industry or sector context.
-
B.
sponsorIndustry
chosen
Indicates that an entity acts as a sponsor for, or is financially or organizationally supporting, a particular industry or industrial sector.
-
C.
supportedIndustry
Indicates that one entity provides backing, resources, or services to help sustain or advance a particular industry.
-
D.
sponsoringOrganizationType
Indicates the kind or category of organization that provides sponsorship or support in the described relationship or activity.
-
E.
sponsorInHouse
Indicates that one entity formally supports, promotes, or funds another entity within the same organization, institution, or internal setting.
- 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_69d8278d25148190abf1a8c8f5f533ad |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de6582f5308190969f4cfd724d9139 |
completed | April 14, 2026, 4:04 p.m. |
| PD | Predicate disambiguation | batch_69de2a7d586c8190846ff242bbf5ac53 |
completed | April 14, 2026, 11:52 a.m. |
Created at: April 10, 2026, 1:10 a.m.