Triple
T16891917
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Soviet Union topped overall medal table |
E424193
|
entity |
| Predicate | secondPlaceGoldMedals |
P18706
|
FINISHED |
| Object | 9 |
—
|
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: 9 | Statement: [Soviet Union topped overall medal table, secondPlaceGoldMedals, 9]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: secondPlaceGoldMedals Context triple: [Soviet Union topped overall medal table, secondPlaceGoldMedals, 9]
-
A.
secondRankedNationByGoldMedals
chosen
Indicates that a nation is ranked second among all nations when ordered by the number of gold medals won.
-
B.
olympicSilverMedals
Indicates that the subject has won one or more silver medals at the Olympic Games.
-
C.
secondMedalCountry
Indicates the country that received the second-place medal in a given event or competition.
-
D.
silverMedalist
Indicates that an entity finished in second place in a competition or event, earning the silver medal.
-
E.
worldChampionshipSilverMedals
Indicates that the subject has won one or more silver medals at a world championship competition.
- 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_69d889da3e8c8190a2b118f383f0beac |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e3bbc5a5308190937ebd05356bd91d |
completed | April 18, 2026, 5:13 p.m. |
| PD | Predicate disambiguation | batch_69e32b90ec3c819099c51bb7baf2984c |
completed | April 18, 2026, 6:58 a.m. |
Created at: April 10, 2026, 5:29 a.m.