Triple
T25266470
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | City of Miami government |
E633443
|
entity |
| Predicate | numberOfCityCommissionDistricts |
P1679
|
FINISHED |
| Object | 5 |
—
|
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: 5 | Statement: [City of Miami government, numberOfCityCommissionDistricts, 5]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfCityCommissionDistricts Context triple: [City of Miami government, numberOfCityCommissionDistricts, 5]
-
A.
numberOfDistricts
chosen
Indicates the total count of districts associated with a given entity or area.
-
B.
numberOfDistrictMembers
Indicates the relationship that specifies how many members are associated with a given district.
-
C.
numberOfDistrictCourts
Indicates the total count of district courts associated with a given entity.
-
D.
hasUrbanDistrictCount
Indicates the number of urban districts associated with a given entity.
-
E.
numberOfCommissioners
Indicates the specific count of commissioners associated with a given entity or context.
- 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_69e75a92f48881909974ff9c11150a2e |
completed | April 21, 2026, 11:08 a.m. |
| NER | Named-entity recognition | batch_69f71f8ee0688190bd025f27993452d3 |
completed | May 3, 2026, 10:12 a.m. |
| PD | Predicate disambiguation | batch_69f71cc405c08190863565609a4c8499 |
completed | May 3, 2026, 10 a.m. |
Created at: April 21, 2026, 1:16 p.m.