Triple
T414792
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1972 Summer Olympics |
E9567
|
entity |
| Predicate | topRankedNationTotalMedals |
P10423
|
FINISHED |
| Object | 99 |
—
|
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: 99 | Statement: [1972 Summer Olympics, topRankedNationTotalMedals, 99]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: topRankedNationTotalMedals Context triple: [1972 Summer Olympics, topRankedNationTotalMedals, 99]
-
A.
hostCountryMedalRank
Indicates the ranking position of the host country in the overall medal standings for a given sporting event or competition.
-
B.
topGoldMedalCountry
Indicates that a country is the one with the highest number of gold medals in a given competition or context.
-
C.
topMedalCountry
chosen
Indicates that a country is the one with the highest total medal count (or ranking) in a given competition or event.
-
D.
medalTableLeader
Indicates that an entity is currently leading the medal table, typically having the highest overall medal standing compared to others.
-
E.
thirdInMedalTable
Indicates that an entity finished in third place in a ranking of medal counts (a medal table), typically in a competition or multi-sport 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_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. |
Created at: Feb. 28, 2026, 1:09 p.m.