Triple
T35111100
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lions of Teranga |
E1013288
|
entity |
| Predicate | coachSince |
P182535
|
FINISHED |
| Object | 2015 |
—
|
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: 2015 | Statement: [Lions of Teranga, coachSince, 2015]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: coachSince Context triple: [Lions of Teranga, coachSince, 2015]
-
A.
coachProfession
Indicates that one entity serves professionally as a coach in relation to the other entity.
-
B.
conferenceCoach
Indicates a person who provides guidance, training, or mentorship to participants in the context of a conference or similar professional gathering.
-
C.
coachSchool
Indicates that a person serves as a coach for a particular school or educational institution.
-
D.
coachOf
Indicates that one entity serves as the coach (trainer or manager) of another entity, typically a person or team.
-
E.
coachesFor
Indicates that one entity serves as a coach or trainer for another entity, typically providing guidance, instruction, or leadership in a specific activity or domain.
- 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_69f76dd659d08190bcdc00d37caafb62 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f78dbf72648190a4971a558e9d1889 |
completed | May 3, 2026, 6:02 p.m. |
| PD | Predicate disambiguation | batch_69f78b8f4cc08190b49fccd798cb25d7 |
completed | May 3, 2026, 5:53 p.m. |
| PDg | Predicate description generation | batch_69f78ce43094819093857fc99f269afe |
completed | May 3, 2026, 5:59 p.m. |
Created at: May 3, 2026, 4:01 p.m.