Triple
T4376945
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | GAIS |
E99029
|
entity |
| Predicate | hasProfessionalTeamIn |
P48352
|
FINISHED |
| Object | football |
—
|
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: football | Statement: [GAIS, hasProfessionalTeamIn, football]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasProfessionalTeamIn Context triple: [GAIS, hasProfessionalTeamIn, football]
-
A.
hasProfessionalLeague
Indicates that an entity is associated with or participates in a recognized professional sports league.
-
B.
hasSportsTeam
Indicates that an entity possesses, sponsors, or is represented by a sports team.
-
C.
hasMajorSportsTeam
Indicates that a location is home to at least one prominent, officially recognized sports team, typically in a major professional or collegiate league.
-
D.
leagueFounded
Indicates that a particular sports league was established or came into existence on a specific date or in a specific year.
-
E.
sportOfReferencedTeam
chosen
Indicates that the subject is the sport played by, or associated with, the referenced team.
- 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_69b3454ea8f48190a49c2436624d6ef6 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3523ed220819090cef1a7933489d9 |
completed | March 12, 2026, 11:54 p.m. |
| PD | Predicate disambiguation | batch_69b34f557fe8819085032bf7f0cea5dc |
completed | March 12, 2026, 11:42 p.m. |
Created at: March 12, 2026, 11:18 p.m.