Triple
T11804247
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wanda Rutkiewicz |
E280702
|
entity |
| Predicate | hasGenreOfAchievement |
P74191
|
FINISHED |
| Object | alpine-style ascents |
—
|
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: alpine-style ascents | Statement: [Wanda Rutkiewicz, hasGenreOfAchievement, alpine-style ascents]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGenreOfAchievement Context triple: [Wanda Rutkiewicz, hasGenreOfAchievement, alpine-style ascents]
-
A.
hasAchievementType
chosen
Indicates that an achievement is classified under a specific type or category of achievement.
-
B.
genreOfAwards
Indicates the type or category of awards associated with a given work, event, or entity.
-
C.
hasStageGenre
Indicates a relationship where a stage production or performance is associated with a particular theatrical or performance genre.
-
D.
hasGenreInRoles
Indicates that an entity participates in roles associated with a particular genre or set of genres.
-
E.
associatedAchievement
Indicates a relationship where one entity is linked to, or recognized in connection with, a particular achievement.
- 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_69d6ab26aae88190b2489efcb2a24234 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8a658f918819092c2db05fe2ab0ce |
completed | April 10, 2026, 7:27 a.m. |
| PD | Predicate disambiguation | batch_69d8a24e9a088190aff7932d1ff93dbf |
completed | April 10, 2026, 7:10 a.m. |
Created at: April 8, 2026, 9:42 p.m.