Triple
T31914259
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New York State Senate District 24 |
E814778
|
entity |
| Predicate | countyCode |
P10086
|
FINISHED |
| Object | Richmond County |
—
|
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: Richmond County | Statement: [New York State Senate District 24, countyCode, Richmond County]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: countyCode Context triple: [New York State Senate District 24, countyCode, Richmond County]
-
A.
districtCode
Indicates that an entity is associated with, or identified by, a specific administrative district code.
-
B.
areaCode
Indicates that a location, phone number, or region is associated with a specific telephone area code.
-
C.
cityCode
Indicates the standardized code that uniquely identifies a particular city.
-
D.
hasCountyCode
chosen
Indicates that an entity is associated with a specific county identified by a standardized county code.
-
E.
provinceNumber
Indicates a relationship where an entity is assigned a specific numerical identifier corresponding to a province.
- 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_69f348f109d88190b5005372c53d2fcd |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_6a000fda03948190881b7275f249768f |
completed | May 10, 2026, 4:55 a.m. |
| PD | Predicate disambiguation | batch_6a000f607f1881908ee750d58da91690 |
completed | May 10, 2026, 4:53 a.m. |
Created at: May 1, 2026, 12:01 a.m.