Triple
T27966505
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Devil Girls |
E704736
|
entity |
| Predicate | hasFictionalCoach |
P53221
|
FINISHED |
| Object | Sloane Hayes |
—
|
NE NERFINISHED |
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: Sloane Hayes | Statement: [Devil Girls, hasFictionalCoach, Sloane Hayes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFictionalCoach Context triple: [Devil Girls, hasFictionalCoach, Sloane Hayes]
-
A.
hasCoachCharacter
chosen
Indicates that one entity serves as the coach or trainer character associated with another entity.
-
B.
featuredCoach
Indicates that a particular coach is highlighted or given special prominence within a specific context or collection.
-
C.
hasRugbyCoachCharacter
Indicates that an entity has, is associated with, or is characterized by a rugby coach as a defining attribute or role.
-
D.
coachOf
Indicates that one entity serves as the coach (trainer or manager) of another entity, typically a person or team.
-
E.
hasFictionalDriver
Indicates that an entity (such as a vehicle or object) is associated with a driver who is a fictional or imaginary character.
- 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_69ef841061e48190b5570f9562f7434d |
completed | April 27, 2026, 3:43 p.m. |
| NER | Named-entity recognition | batch_69fcdf2394748190b35cead3e208447d |
completed | May 7, 2026, 6:51 p.m. |
| PD | Predicate disambiguation | batch_69fcdbe344ec8190a0471911952f4b82 |
completed | May 7, 2026, 6:37 p.m. |
Created at: April 27, 2026, 7:35 p.m.