Triple
T4224479
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alexander Matthew Busby |
E94420
|
entity |
| Predicate | teamStyle |
P55413
|
FINISHED |
| Object | attacking 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: attacking football | Statement: [Alexander Matthew Busby, teamStyle, attacking football]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: teamStyle Context triple: [Alexander Matthew Busby, teamStyle, attacking football]
-
A.
teamColor
Indicates the association between a team and the color that represents or identifies it.
-
B.
teamRepresentation
Indicates that one entity serves as the official representative or embodiment of a team in a given context or activity.
-
C.
teamName
Indicates the relationship that assigns or associates a specific name with a particular team.
-
D.
featuredTeam
Indicates that a particular team is highlighted or given special prominence in a given context or presentation.
-
E.
typicalTeamDesignation
Indicates the standard or commonly used team name or label that is typically assigned to an entity.
- F. None of above. chosen
Provenance (4 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_69b3453700a08190ae88792e3dc63207 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b34e4bf6088190926b982039a12079 |
completed | March 12, 2026, 11:37 p.m. |
| PD | Predicate disambiguation | batch_69b347f1d7b48190bd8974c03c7dc937 |
completed | March 12, 2026, 11:10 p.m. |
| PDg | Predicate description generation | batch_69b34e4ace648190acf911853d4fcf86 |
completed | March 12, 2026, 11:37 p.m. |
Created at: March 12, 2026, 11:04 p.m.