Triple
T69049
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | WSH |
E1380
|
entity |
| Predicate | teamType |
P2705
|
FINISHED |
| Object | professional football team |
—
|
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: professional football team | Statement: [WSH, teamType, professional football team]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: teamType Context triple: [WSH, teamType, professional football team]
-
A.
typeOfTeams
chosen
Indicates the categories or kinds of teams to which an entity or group of entities belongs.
-
B.
team2
Indicates that the second team involved in a competitive or collaborative context is associated with a given entity or event.
-
C.
team1
Indicates that the referenced entity is the first team or side participating in a competitive or relational context.
-
D.
teamDivision
Indicates how a larger team is split into smaller subgroups or units for organization or collaboration.
-
E.
MVPTeam
Indicates that a particular team is recognized as having the Most Valuable Player (MVP) or is designated as the MVP team in a given context or competition.
- 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_69a24c06b3bc8190aa4ac89026115efc |
completed | Feb. 28, 2026, 1:59 a.m. |
| NER | Named-entity recognition | batch_69a24fd16c248190a6ee4cd96c388772 |
completed | Feb. 28, 2026, 2:15 a.m. |
| PD | Predicate disambiguation | batch_69a24ea8cfd081908a26edad2473dde3 |
completed | Feb. 28, 2026, 2:10 a.m. |
Created at: Feb. 28, 2026, 2:03 a.m.