Triple
T37346323
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Korbut flip on balance beam |
E927184
|
entity |
| Predicate | associatedGymnast |
P205843
|
FINISHED |
| Object | Olga Korbut |
E52657
|
NE 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: Olga Korbut | Statement: [Korbut flip on balance beam, associatedGymnast, Olga Korbut]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedGymnast Context triple: [Korbut flip on balance beam, associatedGymnast, Olga Korbut]
-
A.
gymnasticsStar
Indicates that one entity is recognized as an outstanding or star performer in gymnastics.
-
B.
associatedWithGym
Indicates a relationship where an entity has a connection or affiliation with a gym, such as membership, usage, or formal partnership.
-
C.
gymnasticsTeam
Indicates that one entity is a gymnastics team associated with, composed of, or representing the other entity.
-
D.
associatedWrestler
Indicates that one entity is connected or linked to a particular wrestler, typically through participation, representation, or relevant involvement.
-
E.
gymnasticsApparatusSpecialty
Indicates that an entity specializes in or is particularly skilled at using a specific gymnastics apparatus.
- F. None of above. chosen
Provenance (5 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_69f76eb5e034819088e53ab5b7909a68 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_6a037cad051c8190b28b354b89208574 |
completed | May 12, 2026, 7:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a40823c560081908d137a2108e1703e |
completed | June 28, 2026, 2:09 a.m. |
| PD | Predicate disambiguation | batch_6a037a13a1308190a202df66f4781855 |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c842b2c819082f1d2db995ac2eb |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 3, 2026, 4:16 p.m.