Triple
T3768196
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | L’Auto |
E82730
|
entity |
| Predicate | inspiredTourDeFranceJerseyColor |
P16707
|
FINISHED |
| Object | yellow jersey |
—
|
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: yellow jersey | Statement: [L’Auto, inspiredTourDeFranceJerseyColor, yellow jersey]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: inspiredTourDeFranceJerseyColor Context triple: [L’Auto, inspiredTourDeFranceJerseyColor, yellow jersey]
-
A.
mountainsJerseyColor
Indicates the color of the jersey worn by the leader of the mountains classification (best climber) in a cycling race.
-
B.
jerseyColorGeneralClassification
chosen
Indicates the color of the jersey worn by the leader of the general classification in a race or competition.
-
C.
youngRiderJerseyColor
Indicates the color of the jersey awarded to the best young rider in a cycling competition.
-
D.
jerseyDesignInspiredBy
Indicates that the design of a jersey is based on, influenced by, or derived from another design, theme, or source.
-
E.
jerseyColorYoungRiderClassification
Indicates the color of the jersey worn by the leader of the young rider classification in a cycling race.
- 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_69ad8b207b0081909d2b48843fbd8795 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adcc2bdf6c819088d3c6ace83ca5ea |
completed | March 8, 2026, 7:21 p.m. |
| PD | Predicate disambiguation | batch_69adc04ec36c8190bd5b944d4f4d32aa |
completed | March 8, 2026, 6:30 p.m. |
Created at: March 8, 2026, 3:35 p.m.