Triple
T27626718
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United States at the Winter Olympics |
E696227
|
entity |
| Predicate | firstHostYear |
P199482
|
FINISHED |
| Object | 1932 |
—
|
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: 1932 | Statement: [United States at the Winter Olympics, firstHostYear, 1932]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstHostYear Context triple: [United States at the Winter Olympics, firstHostYear, 1932]
-
A.
firstYearHostVenue
Indicates that a venue is the location where an event or competition was hosted in its first year.
-
B.
firstWinnerYear
Indicates the year in which an entity first won a particular competition, award, or title.
-
C.
firstTourYear
Indicates the year in which an entity (such as a performer, team, or event) undertook its first tour.
-
D.
firstEngagementYear
Indicates the calendar year in which an entity first became engaged in a specified relationship, activity, or involvement.
-
E.
firstKnownTournamentYear
Indicates the year in which a tournament was first known to have been held.
- 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_69ef59092c8881908114ad184248cc46 |
completed | April 27, 2026, 12:39 p.m. |
| NER | Named-entity recognition | batch_69ff3e1762d8819089a60e402e682817 |
completed | May 9, 2026, 2 p.m. |
| PD | Predicate disambiguation | batch_69ff3d8c6f308190a0646b1432752eb8 |
completed | May 9, 2026, 1:58 p.m. |
| PDg | Predicate description generation | batch_69ff3e16527c81908c8d89da704ce012 |
completed | May 9, 2026, 2 p.m. |
Created at: April 27, 2026, 2:18 p.m.