Triple
T24048041
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SRAIL |
E595575
|
entity |
| Predicate | hasListingVenueCity |
P154662
|
FINISHED |
| Object | Zurich |
—
|
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: Zurich | Statement: [SRAIL, hasListingVenueCity, Zurich]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasListingVenueCity Context triple: [SRAIL, hasListingVenueCity, Zurich]
-
A.
hasListingVenue
Indicates that an item, event, or offering is associated with the specific venue where it is listed or made available.
-
B.
operatesVenueInCity
Indicates that an entity operates or manages a venue located within a specified city.
-
C.
hasVenueIn
Indicates that an event, activity, or occurrence takes place at a specific venue located within a particular geographic area or location.
-
D.
hasVenueFor
Indicates that one entity provides or serves as the location or setting where an event, activity, or function takes place for another entity.
-
E.
hasVenueName
Indicates that an entity has a specific name used to identify the venue where an event or activity takes place.
- 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_69e288c06a908190899cad4531f32c9a |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f1d9cd50648190b009e97e5be53e8b |
completed | April 29, 2026, 10:13 a.m. |
| PD | Predicate disambiguation | batch_69f1764345388190a3102b62ddb729b4 |
completed | April 29, 2026, 3:08 a.m. |
| PDg | Predicate description generation | batch_69f1785afe3c81909be28986ffe944bf |
completed | April 29, 2026, 3:17 a.m. |
Created at: April 17, 2026, 10:18 p.m.