Triple
T23013300
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Firestone Grand Prix of St. Petersburg |
E572962
|
entity |
| Predicate | cityUsesStreetsForCircuit |
P121309
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Firestone Grand Prix of St. Petersburg, cityUsesStreetsForCircuit, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cityUsesStreetsForCircuit Context triple: [Firestone Grand Prix of St. Petersburg, cityUsesStreetsForCircuit, yes]
-
A.
cityStreetUsed
chosen
Indicates that a particular city street is utilized or traversed in the course of some activity, route, or event.
-
B.
streetNetwork
Indicates the layout and connectivity relationships among streets within a geographic area, including how roads intersect, link, and form a navigable network.
-
C.
hasNumberOfStreets
Indicates the relationship that specifies how many streets are associated with or contained within a given entity.
-
D.
streetNetworkIncludes
Indicates that a given street network contains or encompasses a specified street segment, feature, or component as part of its structure.
-
E.
hasCobbledStreets
Indicates that a place possesses streets that are surfaced with cobblestones.
- 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_69e245b764cc8190a51be76f1d9611e1 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f183e300008190bb12c6388a8b3280 |
completed | April 29, 2026, 4:06 a.m. |
| PD | Predicate disambiguation | batch_69ef3b9cd5488190bcd23183179f48cd |
completed | April 27, 2026, 10:34 a.m. |
Created at: April 17, 2026, 3:51 p.m.