Triple
T23380400
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ontario gaming market |
E593727
|
entity |
| Predicate | notableCityMarket |
P82646
|
FINISHED |
| Object | Toronto |
—
|
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: Toronto | Statement: [Ontario gaming market, notableCityMarket, Toronto]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableCityMarket Context triple: [Ontario gaming market, notableCityMarket, Toronto]
-
A.
famousMarket
Indicates that a market is widely known and recognized, typically for its popularity, historical significance, or distinctive offerings.
-
B.
marketCity
chosen
Indicates that a city serves as a primary marketplace or commercial center for a given region or entity.
-
C.
marketsIn
Indicates that one entity promotes, sells, or offers another entity’s products or services within a particular market or geographic area.
-
D.
notableInCity
Indicates that an entity is particularly prominent, recognized, or significant within a specific city.
-
E.
notableCityCenter
Indicates that a location serves as a prominent or significant central area within a city.
- 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_69e25d268a50819095f2fd479da8ef3f |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1a3b6ddfc8190a23d291286f3fe42 |
completed | April 29, 2026, 6:22 a.m. |
| PD | Predicate disambiguation | batch_69f061dde2e481908308952f9c0d3c2e |
completed | April 28, 2026, 7:29 a.m. |
Created at: April 17, 2026, 5:34 p.m.