Triple
T25314883
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brisbane Lions (AFLW) |
E634707
|
entity |
| Predicate | coachAppointmentYear |
P59808
|
FINISHED |
| Object | 2016 |
—
|
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: 2016 | Statement: [Brisbane Lions (AFLW), coachAppointmentYear, 2016]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: coachAppointmentYear Context triple: [Brisbane Lions (AFLW), coachAppointmentYear, 2016]
-
A.
coachStartYear
chosen
Indicates the year in which a person began serving in a coaching role for a particular team or organization.
-
B.
UNAppointmentYear
Indicates the year in which an entity was appointed to a position within the United Nations.
-
C.
coachOfYearSeason
Indicates that a person was recognized as the coach of the year for a specific sports season.
-
D.
coachTenureIncludes
Indicates that a coach’s period of service or employment with a team or organization covers or includes a specified time span or event.
-
E.
designationYear
Indicates the year in which something was formally designated, assigned, or given an official status.
- 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_69e75a9847c08190bb02990d06d5ffb7 |
completed | April 21, 2026, 11:08 a.m. |
| NER | Named-entity recognition | batch_69f49688f3b881909a7bb16aeea95fbe |
completed | May 1, 2026, 12:03 p.m. |
| PD | Predicate disambiguation | batch_69f45d06d0388190b36ecde92013624a |
completed | May 1, 2026, 7:57 a.m. |
Created at: April 21, 2026, 1:27 p.m.