Triple
T36173063
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kamaishi |
E1046197
|
entity |
| Predicate | wasHostCityOf |
P7898
|
FINISHED |
| Object | 2019 Rugby World Cup matches |
—
|
NE NERFINISHED |
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: 2019 Rugby World Cup matches | Statement: [Kamaishi, wasHostCityOf, 2019 Rugby World Cup matches]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wasHostCityOf Context triple: [Kamaishi, wasHostCityOf, 2019 Rugby World Cup matches]
-
A.
hasHostCity
chosen
Indicates that a particular event, organization, or activity is located in or officially hosted by a specific city.
-
B.
notableFormerHostCity
Indicates that a city previously hosted a notable event or series of events associated with the subject.
-
C.
OlympicHostCity
Indicates that a city has been officially selected to host and organize a particular edition of the Olympic Games.
-
D.
inauguralHostCity
Indicates the city that first hosted a particular event, competition, or series.
-
E.
hostCityOfEventParticipatedIn
Indicates that a city is the location where a particular event took place in which an entity participated.
- 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_69f76e396bc88190b99d221bff9be27a |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7b69b333081909cadbed3fcb8ecf5 |
completed | May 3, 2026, 8:56 p.m. |
| PD | Predicate disambiguation | batch_69f7b4c2a5f8819094ad4621d7b97e0c |
completed | May 3, 2026, 8:49 p.m. |
Created at: May 3, 2026, 4:08 p.m.