Triple
T15013906
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Margzetta Frazier |
E377907
|
entity |
| Predicate | hasEventSpecialty |
P37115
|
FINISHED |
| Object | floor exercise |
—
|
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: floor exercise | Statement: [Margzetta Frazier, hasEventSpecialty, floor exercise]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEventSpecialty Context triple: [Margzetta Frazier, hasEventSpecialty, floor exercise]
-
A.
eventSpecialty
chosen
Indicates the specific field, theme, or area of focus that an event is primarily concerned with.
-
B.
hasSpecialty
Indicates that an entity possesses a particular area of expertise, focus, or professional specialization.
-
C.
specialtyEvent
Indicates that an event is designated as a special or distinctive occurrence, often differing from regular or routine events in nature or purpose.
-
D.
hasSpecialist
Indicates that one entity is associated with or assigned to a specialist entity that provides expert support, service, or oversight for it.
-
E.
hasSpecialtyChannel
Indicates that one entity provides or is associated with a dedicated channel focused on a particular specialty or subject area for another entity.
- 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_69d85cd3a3c881908c71fc424d459c17 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded7623c3c819092ca36b358b01842 |
completed | April 15, 2026, 12:10 a.m. |
| PD | Predicate disambiguation | batch_69de9a6531a88190acde65199a477350 |
completed | April 14, 2026, 7:49 p.m. |
Created at: April 10, 2026, 2:55 a.m.