Triple
T11748238
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Park County, Wyoming |
E279337
|
entity |
| Predicate | countyNumber |
P19171
|
FINISHED |
| Object | 11 (Wyoming license plate code) |
—
|
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: 11 (Wyoming license plate code) | Statement: [Park County, Wyoming, countyNumber, 11 (Wyoming license plate code)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: countyNumber Context triple: [Park County, Wyoming, countyNumber, 11 (Wyoming license plate code)]
-
A.
numberPerCounty
Indicates the quantity or count of something associated with each individual county.
-
B.
regionNumber
chosen
Indicates that an entity is assigned to or associated with a specific numbered region within a larger spatial or organizational division.
-
C.
provinceNumber
Indicates a relationship where an entity is assigned a specific numerical identifier corresponding to a province.
-
D.
hasNumberOfCounties
Indicates the relationship that specifies how many counties are associated with or contained within a given entity.
-
E.
countyNumberInStateFormation
Indicates the ordinal position a county held among all counties created within a particular state at the time of that state's formation.
- 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_69d6ab01038c819080714901502c84fc |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a50763a081908597da118bd0a64e |
completed | April 10, 2026, 7:21 a.m. |
| PD | Predicate disambiguation | batch_69d88a813cc48190a3dfdc60e8af80ae |
completed | April 10, 2026, 5:28 a.m. |
Created at: April 8, 2026, 9:41 p.m.