Triple
T14145903
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jean Stablinski |
E350547
|
entity |
| Predicate | majorResult |
P112995
|
FINISHED |
| Object | overall winner of 1958 Vuelta a España |
—
|
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: overall winner of 1958 Vuelta a España | Statement: [Jean Stablinski, majorResult, overall winner of 1958 Vuelta a España]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: majorResult Context triple: [Jean Stablinski, majorResult, overall winner of 1958 Vuelta a España]
-
A.
major
Indicates that one entity is the primary field of academic specialization or main area of study for another entity.
-
B.
majorStatus
Indicates that an entity holds primary or most significant status relative to others in a given context.
-
C.
majorFor
Indicates that an academic program, field of study, or specialization is the primary major associated with a particular student or degree.
-
D.
majorExamination
Indicates that an entity is formally assessed through a significant or high-stakes examination or test.
-
E.
majorSee
Indicates that one entity serves as the primary or most important location where another entity is based, operates, or is centered.
- 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_69d827865f608190b311820428ae027b |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de612266248190a8591b646fe30ae6 |
completed | April 14, 2026, 3:45 p.m. |
| PD | Predicate disambiguation | batch_69de05b5e7a08190a16be9ad8b92b80c |
completed | April 14, 2026, 9:15 a.m. |
| PDg | Predicate description generation | batch_69de239a02e881909b0e2679487e4ab2 |
completed | April 14, 2026, 11:23 a.m. |
Created at: April 10, 2026, 12:53 a.m.