Triple
T1519594
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Florida local governments |
E32196
|
entity |
| Predicate | numberOfCounties |
P27148
|
FINISHED |
| Object | 67 |
—
|
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: 67 | Statement: [Florida local governments, numberOfCounties, 67]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfCounties Context triple: [Florida local governments, numberOfCounties, 67]
-
A.
hasNumberOfCounties
chosen
Indicates the relationship that specifies how many counties are associated with or contained within a given entity.
-
B.
numberOfDistricts
Indicates the total count of districts associated with a given entity or area.
-
C.
numberOfStates
Indicates the total count of distinct states or conditions associated with an entity or system.
-
D.
includesCounty
Indicates that a larger geographic or administrative region contains or encompasses a specific county within its boundaries.
-
E.
hasCountyCode
Indicates that an entity is associated with a specific county identified by a standardized county code.
- 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_69a885e9b0ac819093a9806ad0efc82c |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a93d4756888190bf3872154de11539 |
completed | March 5, 2026, 8:22 a.m. |
| PD | Predicate disambiguation | batch_69a907ac7ea081908dd95bb5cc3b9847 |
completed | March 5, 2026, 4:33 a.m. |
Created at: March 4, 2026, 7:26 p.m.