Triple
T22888214
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Best FIFA Women’s Coach |
E567662
|
entity |
| Predicate | usesCalendarYear |
P7173
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Best FIFA Women’s Coach, usesCalendarYear, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesCalendarYear Context triple: [Best FIFA Women’s Coach, usesCalendarYear, true]
-
A.
usesCalendar
Indicates that an entity employs or relies on a calendar system for organizing, tracking, or scheduling dates and events.
-
B.
usesCalendarEvent
Indicates that one entity makes use of, interacts with, or relies on a specific calendar event.
-
C.
hasCalendarFunction
Indicates that an entity possesses or supports a calendar-related capability or functionality.
-
D.
yearType
chosen
Indicates the classification or category assigned to a specific year (e.g., academic, fiscal, calendar, leap).
-
E.
includesYear
Indicates that one entity contains, references, or is associated with a specific calendar year as part of its information or scope.
- 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_69e2458a92ec81908fc1cd5f6407d2ab |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17fc2adb4819081bce7e6849ba31a |
completed | April 29, 2026, 3:49 a.m. |
| PD | Predicate disambiguation | batch_69ef3b6b2e2481908258156937b5a745 |
completed | April 27, 2026, 10:33 a.m. |
Created at: April 17, 2026, 3:40 p.m.