Triple
T22089695
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Frisco City Hall |
E545879
|
entity |
| Predicate | locatedInMunicipality |
P40
|
FINISHED |
| Object | Frisco |
—
|
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: Frisco | Statement: [Frisco City Hall, locatedInMunicipality, Frisco]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Frisco Context triple: [Frisco City Hall, locatedInMunicipality, Frisco]
-
A.
Frisco
Frisco is the popular nickname for the historic St. Louis–San Francisco Railway, a major American railroad that operated across the Midwest and South.
-
B.
Frisco
Frisco is a small unincorporated village and popular beach destination on North Carolina’s Outer Banks.
-
C.
Frisco, Texas
chosen
Frisco, Texas is a rapidly growing suburban city in the Dallas–Fort Worth metropolitan area known for its sports venues, retail centers, and family-friendly communities.
-
D.
Grand Prairie
Grand Prairie is a mid-sized suburban city in the Dallas–Fort Worth metropolitan area known for its family attractions, parks, and growing residential communities.
-
E.
San Antonio
San Antonio is a coastal municipality in the Philippine province of Zambales known for its beaches, coves, and nearby island-hopping destinations.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e11e36d03c8190a83a1ba802b7231b |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f128e47ba08190a208af72a7cc176f |
completed | April 28, 2026, 9:38 p.m. |
Created at: April 16, 2026, 8:29 p.m.