Triple
T28551171
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marlies Schild |
E722887
|
entity |
| Predicate | wonWorldChampionshipTitleIn |
P104075
|
FINISHED |
| Object | slalom |
—
|
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: slalom | Statement: [Marlies Schild, wonWorldChampionshipTitleIn, slalom]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wonWorldChampionshipTitleIn Context triple: [Marlies Schild, wonWorldChampionshipTitleIn, slalom]
-
A.
wonWorldTitleIn
chosen
Indicates that an entity achieved victory in a world championship title in a specified competition or year.
-
B.
wonNationalTitle
Indicates that an entity has achieved first place or championship status in a competition at the national level.
-
C.
wonInternationalTitle
Indicates that an entity has achieved victory in a competition or event that is recognized at an international level, earning an international title.
-
D.
wonTitleWith
Indicates that an entity secured a specific title, award, or championship while being associated with or representing another entity (such as a team, organization, or group).
-
E.
wonTitleFrom
Indicates that one entity obtained a title or championship by defeating or surpassing another specific entity who previously held it.
- 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_69f01a60204481909af1bb76247b8221 |
completed | April 28, 2026, 2:24 a.m. |
| NER | Named-entity recognition | batch_69f6504c5e1c8190903e5c4aeac37a30 |
completed | May 2, 2026, 7:28 p.m. |
| PD | Predicate disambiguation | batch_69f64cb0d8008190912e1430cfaf92aa |
completed | May 2, 2026, 7:12 p.m. |
Created at: April 28, 2026, 3:42 a.m.