Triple
T10865566
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gabriel Brener |
E256520
|
entity |
| Predicate | sportInvestment |
P71678
|
FINISHED |
| Object | soccer |
—
|
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: soccer | Statement: [Gabriel Brener, sportInvestment, soccer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sportInvestment Context triple: [Gabriel Brener, sportInvestment, soccer]
-
A.
sportsMarketFor
Indicates a market or commercial context in which a particular sport, sporting event, or sports-related product is bought, sold, traded, or otherwise economically transacted.
-
B.
sportIndustry
chosen
Indicates a relationship where an entity is involved in, associated with, or part of the sports industry or sports-related economic sector.
-
C.
sportOwned
Indicates that one entity possesses ownership or control over a particular sport.
-
D.
otherSportIndustry
Indicates a relationship where an entity is involved in, associated with, or belongs to a sports-related industry other than the primary or specified one.
-
E.
sponsorSport
Indicates that one entity financially or materially supports a sport or sporting activity, typically in exchange for promotion or association.
- 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_69d6aa83d1448190a66d93c32394d21f |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d7516cebe881909ed358a7641f6a12 |
completed | April 9, 2026, 7:12 a.m. |
| PD | Predicate disambiguation | batch_69d70d308dfc81908792f98cfb871392 |
completed | April 9, 2026, 2:21 a.m. |
Created at: April 8, 2026, 9:20 p.m.