Triple
T30956857
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Neve and Gliz |
E788698
|
entity |
| Predicate | introducedForEventInCity |
P192435
|
FINISHED |
| Object | Turin |
—
|
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: Turin | Statement: [Neve and Gliz, introducedForEventInCity, Turin]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: introducedForEventInCity Context triple: [Neve and Gliz, introducedForEventInCity, Turin]
-
A.
associatedCityEvent
Indicates a relationship where a city is linked to, involved in, or serves as the location for a particular event.
-
B.
introducedEvent
Indicates that an entity is responsible for bringing an event into existence or initiating it for the first time.
-
C.
announcedInCity
Indicates that an announcement or declaration was formally made within a particular city.
-
D.
notableEventHostedAtReferredVenue
Indicates that a notable event was hosted at, or took place in, the referenced venue.
-
E.
hostCityOfEventParticipatedIn
Indicates that a city is the location where a particular event took place in which an entity participated.
- 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_69f224c28c1881908c33b45d689f1724 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69fd0b92f42881908cd77e3f058adcc2 |
completed | May 7, 2026, 10 p.m. |
| PD | Predicate disambiguation | batch_69fd0a3d68d4819094d92040f7c48d7c |
completed | May 7, 2026, 9:55 p.m. |
| PDg | Predicate description generation | batch_69fd0b92150881909b1166fe6d09aa19 |
completed | May 7, 2026, 10 p.m. |
Created at: April 29, 2026, 8:54 p.m.