Triple
T414788
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1972 Summer Olympics |
E9567
|
entity |
| Predicate | hostNationGoldMedals |
P14575
|
FINISHED |
| Object | 13 |
—
|
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: 13 | Statement: [1972 Summer Olympics, hostNationGoldMedals, 13]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hostNationGoldMedals Context triple: [1972 Summer Olympics, hostNationGoldMedals, 13]
-
A.
topGoldMedalCountry
Indicates that a country is the one with the highest number of gold medals in a given competition or context.
-
B.
hostCountryMedalRank
Indicates the ranking position of the host country in the overall medal standings for a given sporting event or competition.
-
C.
olympicGoldMedals
Indicates that an entity has won one or more Olympic gold medals.
-
D.
worldChampionshipGoldMedals
Indicates the number of gold medals an entity has won at world championship competitions.
-
E.
USMedalsTotal
Indicates the total number of medals won by the United States in a given competition or event.
- 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_69a2e80111fc8190961d5b7c6154123f |
completed | Feb. 28, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69a2eebde1d881908fb212bfba9d7c67 |
completed | Feb. 28, 2026, 1:33 p.m. |
| PD | Predicate disambiguation | batch_69a2edcff4688190809d83d112ff25a5 |
completed | Feb. 28, 2026, 1:29 p.m. |
| PDg | Predicate description generation | batch_69a2eeb8545c8190a2b8517e7ed5b92e |
completed | Feb. 28, 2026, 1:33 p.m. |
Created at: Feb. 28, 2026, 1:09 p.m.