Triple
T19626113
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1990 Asian Games |
E471138
|
entity |
| Predicate | cityFirstTimeHostingAsianGames |
P10414
|
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: [1990 Asian Games, cityFirstTimeHostingAsianGames, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cityFirstTimeHostingAsianGames Context triple: [1990 Asian Games, cityFirstTimeHostingAsianGames, true]
-
A.
firstIncludedInAsianGames
Indicates the edition of the Asian Games in which an entity (such as a sport or event) was first included in the program.
-
B.
inauguralHostCity
Indicates the city that first hosted a particular event, competition, or series.
-
C.
firstTimeHostCity
chosen
Indicates that a city is serving as the host of an event for the first time.
-
D.
notableFormerHostCity
Indicates that a city previously hosted a notable event or series of events associated with the subject.
-
E.
longtimeHostCity
Indicates that a city has hosted a particular event or activity repeatedly over an extended period of time.
- 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_69d8e511f28481909f4bc3ea9191e54a |
completed | April 10, 2026, 11:54 a.m. |
| NER | Named-entity recognition | batch_69e640e9ff208190afb33c910ed2147b |
completed | April 20, 2026, 3:06 p.m. |
| PD | Predicate disambiguation | batch_69e514e5cb108190ae260e466c447314 |
completed | April 19, 2026, 5:46 p.m. |
Created at: April 10, 2026, 1:44 p.m.