Triple
T428570
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1936 Summer Olympics |
E9663
|
entity |
| Predicate | hostCitySelectionYear |
P13803
|
FINISHED |
| Object | 1931 |
—
|
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: 1931 | Statement: [1936 Summer Olympics, hostCitySelectionYear, 1931]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hostCitySelectionYear Context triple: [1936 Summer Olympics, hostCitySelectionYear, 1931]
-
A.
hostCitySelectionLocation
Indicates the location where the selection of a host city takes place.
-
B.
hasCoHostCity
Indicates that an event is jointly hosted or organized by the specified city alongside one or more other cities.
-
C.
hostCityBidWinner
Indicates that a particular city has been selected as the winning bidder to host a specific event or competition.
-
D.
hasHostCity
Indicates that a particular event, organization, or activity is located in or officially hosted by a specific city.
-
E.
hasTargetCity
Indicates that something is directed toward, intended for, or specifically associated with a particular city as its target.
- 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_69a2e801e1d48190b505d1dd336b52ac |
completed | Feb. 28, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69a2eeecb64c81908c5c83ef7c0181e6 |
completed | Feb. 28, 2026, 1:34 p.m. |
| PD | Predicate disambiguation | batch_69a2edd7a3608190b8785c7b7205f6c1 |
completed | Feb. 28, 2026, 1:29 p.m. |
| PDg | Predicate description generation | batch_69a2eeb93584819082f23eff13e17c4f |
completed | Feb. 28, 2026, 1:33 p.m. |
Created at: Feb. 28, 2026, 1:11 p.m.