Triple
T14956132
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chazz Michael Michaels |
E372931
|
entity |
| Predicate | laterCompetesIn |
P39898
|
FINISHED |
| Object | pairs figure skating |
—
|
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: pairs figure skating | Statement: [Chazz Michael Michaels, laterCompetesIn, pairs figure skating]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: laterCompetesIn Context triple: [Chazz Michael Michaels, laterCompetesIn, pairs figure skating]
-
A.
competeIn
chosen
Indicates that an entity takes part as a contender in a particular event, activity, or domain where performance is compared against others.
-
B.
laterCompetitionName
Indicates that an entity has its name changed to a different one in a subsequent or later competition.
-
C.
hasCompetition
Indicates that one entity is in a state of rivalry or contest with another entity, typically competing for the same goal, resource, or advantage.
-
D.
tieneCompetenciaEn
Indicates that an entity possesses skill, expertise, or competence in a specific area, field, or activity.
-
E.
competedFor
Indicates that an entity took part in a contest, rivalry, or competition in pursuit of another entity (such as a prize, position, or resource).
- 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_69d85cca979481908747d2a81eba1cea |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded6cc73848190ac181782b20dc838 |
completed | April 15, 2026, 12:07 a.m. |
| PD | Predicate disambiguation | batch_69de9a588c2c8190b1245a1c406f447c |
completed | April 14, 2026, 7:49 p.m. |
Created at: April 10, 2026, 2:40 a.m.