Triple
T17831596
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Greenlee County, Arizona |
E445268
|
entity |
| Predicate | countyNumberInArizona |
P106323
|
FINISHED |
| Object | 14 |
—
|
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: 14 | Statement: [Greenlee County, Arizona, countyNumberInArizona, 14]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: countyNumberInArizona Context triple: [Greenlee County, Arizona, countyNumberInArizona, 14]
-
A.
countyNumberInState
chosen
Indicates the ordinal position or identifying number assigned to a county within its state.
-
B.
countyNumberInColorado
Indicates that a given county is assigned a specific official county number within the state of Colorado.
-
C.
countyNumberInStateFormation
Indicates the ordinal position a county held among all counties created within a particular state at the time of that state's formation.
-
D.
numberPerCounty
Indicates the quantity or count of something associated with each individual county.
-
E.
hasCountyNumberInKansas
Indicates that an entity is assigned a specific official county number within the state of Kansas.
- 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_69d8b9f1a6d881909f024bc603111cdb |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e48d248ecc8190b3f0d001b539d960 |
completed | April 19, 2026, 8:07 a.m. |
| PD | Predicate disambiguation | batch_69e3d8e266888190ae976b4b7d5b886f |
completed | April 18, 2026, 7:17 p.m. |
Created at: April 10, 2026, 10:15 a.m.