Triple
T15038633
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Enfield Tennis Academy |
E378542
|
entity |
| Predicate | hasFictionalStaffRole |
P61558
|
FINISHED |
| Object | tennis coach |
—
|
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: tennis coach | Statement: [Enfield Tennis Academy, hasFictionalStaffRole, tennis coach]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFictionalStaffRole Context triple: [Enfield Tennis Academy, hasFictionalStaffRole, tennis coach]
-
A.
hasFictionalStaffMember
chosen
Indicates that an entity includes or employs a staff member who is a fictional character.
-
B.
hasFictionalRole
Indicates that an entity plays or is assigned a specific role within a fictional work or narrative.
-
C.
hasFictionalCoStar
Indicates that one entity appears as a co-star alongside another entity within a fictional work or narrative.
-
D.
hasInUniverseRole
Indicates that an entity holds or performs a specific role or function within a particular fictional or defined universe.
-
E.
hasFictionalPerformer
Indicates that an entity is associated with a performer who is a fictional or imaginary character rather than a real person.
- 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_69d85cd46b2c819090d054c27787f677 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded82cf3848190b0b2b6c9e65bc70b |
completed | April 15, 2026, 12:13 a.m. |
| PD | Predicate disambiguation | batch_69de9a69d7848190b2b4662dd30f20e9 |
completed | April 14, 2026, 7:50 p.m. |
Created at: April 10, 2026, 2:59 a.m.