Triple
T3663615
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paris–Roubaix |
E77707
|
entity |
| Predicate | womenRaceFirstHeld |
P50237
|
FINISHED |
| Object | 2021 |
—
|
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: 2021 | Statement: [Paris–Roubaix, womenRaceFirstHeld, 2021]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: womenRaceFirstHeld Context triple: [Paris–Roubaix, womenRaceFirstHeld, 2021]
-
A.
womenRaceInstanceOf
Indicates that a specific occurrence of a race event is one in which only women participate.
-
B.
firstFemaleHolderDate
Indicates the date on which the first female individual came to hold a given position, title, or role.
-
C.
hasNotableFirstFemaleWinnerYear
Indicates the year in which the first notable female winner associated with an entity achieved her win.
-
D.
leadershipRaceYear
Indicates the year in which a particular leadership race or leadership contest took place.
-
E.
firstRunningWinner
Indicates that the subject is the first entity to win among those participating in a running event or race.
- 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_69ad85dfc4dc8190a441864202ab2a7a |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc3fe5eb08190ab15044acf9ac8a9 |
completed | March 8, 2026, 6:46 p.m. |
| PD | Predicate disambiguation | batch_69adb847e9d881909dad2ffd0f3b6c15 |
completed | March 8, 2026, 5:56 p.m. |
| PDg | Predicate description generation | batch_69adb97cdb788190a5ce96b21bd157ab |
completed | March 8, 2026, 6:01 p.m. |
Created at: March 8, 2026, 3:25 p.m.