Triple
T3464089
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paris–Nice 1961 |
E73093
|
entity |
| Predicate | secondPlaceCountryCode |
P35410
|
FINISHED |
| Object | ITA |
—
|
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: ITA | Statement: [Paris–Nice 1961, secondPlaceCountryCode, ITA]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: secondPlaceCountryCode Context triple: [Paris–Nice 1961, secondPlaceCountryCode, ITA]
-
A.
secondMedalCountry
Indicates the country that received the second-place medal in a given event or competition.
-
B.
secondPlace
Indicates that an entity holds the position of runner-up or finishes in second place in a ranked ordering, competition, or comparison relative to others.
-
C.
secondRankedNationByGoldMedals
Indicates that a nation is ranked second among all nations when ordered by the number of gold medals won.
-
D.
runnerUpCountry
chosen
Indicates the country that finished in second place in a competition or ranking.
-
E.
regionOfRunnerUp
Indicates the geographic region associated with the runner-up in a competition or event.
- 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_69ad85b224d481908ff8be51338d24ff |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adbb0dc100819084bb0c355c7bb15b |
completed | March 8, 2026, 6:08 p.m. |
| PD | Predicate disambiguation | batch_69adae05bb0081909dc7e4779d6e05ef |
completed | March 8, 2026, 5:12 p.m. |
Created at: March 8, 2026, 3:17 p.m.