Triple
T22617678
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gold Cup hydroplane race |
E558190
|
entity |
| Predicate | hasNotableCityNickname |
P74834
|
FINISHED |
| Object | Detroit as the "Gold Cup City" |
—
|
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: Detroit as the "Gold Cup City" | Statement: [Gold Cup hydroplane race, hasNotableCityNickname, Detroit as the "Gold Cup City"]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotableCityNickname Context triple: [Gold Cup hydroplane race, hasNotableCityNickname, Detroit as the "Gold Cup City"]
-
A.
isInCityNicknamed
Indicates that one entity is located in a city that is known by a particular nickname.
-
B.
metropolitanAreaNickname
Indicates that a metropolitan area is known by a particular informal or colloquial nickname.
-
C.
cityNicknameAssociation
chosen
Indicates an associative relationship where a particular nickname is used to refer to or characterize a specific city.
-
D.
cityNickname
Indicates that one entity is commonly used as an informal or alternative name for a city.
-
E.
homeCityLandmarkReferencedInNickname
Indicates that a landmark from a person's home city is mentioned or alluded to in their nickname.
- 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_69e24545a8e08190bfa7482a2c725ff1 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f167ef7a148190870334af9c8b79a4 |
completed | April 29, 2026, 2:07 a.m. |
| PD | Predicate disambiguation | batch_69ee62855558819080da946c7b35a160 |
completed | April 26, 2026, 7:07 p.m. |
Created at: April 17, 2026, 2:59 p.m.