Triple
T1173762
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2018 Winter Olympics |
E24970
|
entity |
| Predicate | firstWinterGamesWithOver100Events |
P26226
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [2018 Winter Olympics, firstWinterGamesWithOver100Events, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstWinterGamesWithOver100Events Context triple: [2018 Winter Olympics, firstWinterGamesWithOver100Events, true]
-
A.
previousWinterOlympics
Indicates that one Winter Olympic Games event directly preceded another in chronological order.
-
B.
firstSummerGamesYear
Indicates the calendar year in which an entity first participated in or hosted the Summer Olympic Games.
-
C.
firstWinterGamesCity
Indicates the city where an entity (such as a country, team, or athlete) first participated in the Winter Olympic Games.
-
D.
olympicGamesNumber
Indicates the specific edition number assigned to a particular occurrence of the Olympic Games.
-
E.
hostCountryFirstTimeWinterGames
Indicates that a country is hosting the Winter Games for the first time in its history.
- 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_69a494082a7c819095004f423f294a64 |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bd53e4b48190abb2167f8074a6bc |
completed | March 1, 2026, 10:27 p.m. |
| PD | Predicate disambiguation | batch_69a4bb5844348190b01ac6506906ba3b |
completed | March 1, 2026, 10:19 p.m. |
| PDg | Predicate description generation | batch_69a4bd52177081908c5cec8e731b836e |
completed | March 1, 2026, 10:27 p.m. |
Created at: March 1, 2026, 7:45 p.m.