Triple
T295110
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1998 Winter Olympics |
E6075
|
entity |
| Predicate | hostCountryPreviousWinterGamesYear |
P10417
|
FINISHED |
| Object | 1972 |
—
|
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: 1972 | Statement: [1998 Winter Olympics, hostCountryPreviousWinterGamesYear, 1972]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hostCountryPreviousWinterGamesYear Context triple: [1998 Winter Olympics, hostCountryPreviousWinterGamesYear, 1972]
-
A.
olympicHostCountry
Indicates that a country served as the official host nation for a particular edition of the Olympic Games.
-
B.
hostCountryNOC
Indicates that a National Olympic Committee (NOC) is the official host country organization for a particular Olympic Games or sporting event.
-
C.
previousWinterOlympics
Indicates that one Winter Olympic Games event directly preceded another in chronological order.
-
D.
hostCityPreviousOlympicsInCity
Indicates that the city served as the host city for a previous edition of the Olympic Games held in that same city.
-
E.
countryAtTheTime
Indicates that an entity is associated with a specific country as it existed at a particular point in time.
- 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_69a2e79114b081909490b3bf5a5dbb51 |
completed | Feb. 28, 2026, 1:03 p.m. |
| NER | Named-entity recognition | batch_69a2e9e273f88190ac5355d1310376ed |
completed | Feb. 28, 2026, 1:13 p.m. |
| PD | Predicate disambiguation | batch_69a2e9368894819093eeae4347dfcc5a |
completed | Feb. 28, 2026, 1:10 p.m. |
| PDg | Predicate description generation | batch_69a2e9e0d85c8190ae52662d83ea67fe |
completed | Feb. 28, 2026, 1:13 p.m. |
Created at: Feb. 28, 2026, 1:06 p.m.