Triple
T22490903
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gro Espeseth |
E556012
|
entity |
| Predicate | olympicChampionIn |
P148420
|
FINISHED |
| Object | women’s association football |
—
|
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: women’s association football | Statement: [Gro Espeseth, olympicChampionIn, women’s association football]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: olympicChampionIn Context triple: [Gro Espeseth, olympicChampionIn, women’s association football]
-
A.
OlympicGoldMedalistFor
Indicates that an entity has won a gold medal at the Olympic Games while representing a specified country, team, or organization.
-
B.
olympicGoldWith
Indicates that the related entities won an Olympic gold medal together, typically as teammates in the same event or competition.
-
C.
OlympicAthleteFor
Indicates a relationship where an athlete competes in the Olympic Games representing a specific country, team, or organization.
-
D.
representedAtOlympics
Indicates that an entity served as an official representative (e.g., athlete, team, or delegation) for another entity at a specific edition of the Olympic Games.
-
E.
olympicGoldMedals
Indicates that an entity has won one or more Olympic gold medals.
- 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_69e11e53897c819088863779f8c50bb0 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15c40930c81908310ac6afd98c62e |
completed | April 29, 2026, 1:17 a.m. |
| PD | Predicate disambiguation | batch_69e898be31448190be5ae7f5656f0497 |
completed | April 22, 2026, 9:45 a.m. |
| PDg | Predicate description generation | batch_69e8aa3b4c288190951cca06d42bea51 |
completed | April 22, 2026, 11 a.m. |
Created at: April 16, 2026, 8:49 p.m.