Triple
T8271371
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tatiana Tarasova |
E193435
|
entity |
| Predicate | numberOfOlympicGoldMedalistsCoached |
P82428
|
FINISHED |
| Object | multiple |
—
|
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: multiple | Statement: [Tatiana Tarasova, numberOfOlympicGoldMedalistsCoached, multiple]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfOlympicGoldMedalistsCoached Context triple: [Tatiana Tarasova, numberOfOlympicGoldMedalistsCoached, multiple]
-
A.
medalWonAsCoach
Indicates that an individual has won a medal in the role of a coach rather than as a competitor.
-
B.
olympicGoldMedals
Indicates that an entity has won one or more Olympic gold medals.
-
C.
historicalPredecessorHasOlympicGoldMedals
Indicates that the earlier historical counterpart of an entity has won one or more Olympic gold medals.
-
D.
hasCoachedFor
Indicates that one entity has served in a coaching role for another entity, such as a team, organization, or individual.
-
E.
notablePlayersCoached
Indicates that a coach has trained or mentored specific players who are considered notable or distinguished in their field.
- F. None of above. chosen
Provenance (4 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_69ca82e14ae481908ffdb822cd2192bc |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb7986f8cc8190a529dda980dd6e98 |
completed | March 31, 2026, 7:36 a.m. |
| PD | Predicate disambiguation | batch_69cb70a4525481909399d313a6247ace |
completed | March 31, 2026, 6:58 a.m. |
| PDg | Predicate description generation | batch_69cb76d648988190ab0669cc0592e827 |
completed | March 31, 2026, 7:25 a.m. |
Created at: March 30, 2026, 5:50 p.m.