Triple
T18340320
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Apache County, Arizona |
E439383
|
entity |
| Predicate | areaRankInArizona |
P21163
|
FINISHED |
| Object | one of the largest counties by area in Arizona |
—
|
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: one of the largest counties by area in Arizona | Statement: [Apache County, Arizona, areaRankInArizona, one of the largest counties by area in Arizona]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: areaRankInArizona Context triple: [Apache County, Arizona, areaRankInArizona, one of the largest counties by area in Arizona]
-
A.
rankInArizonaByPopulation
Indicates the position an entity holds in a ranking of Arizona locations ordered by their population size.
-
B.
areaRankInUS
Indicates the relative position of an entity in a ranking of areas within the United States, based on its size.
-
C.
stateRank
chosen
Indicates the relative position or standing of an entity within a specific state-level ordering or hierarchy.
-
D.
areaRank
Indicates the relative ordering or position of an entity based on the size of its area compared to others.
-
E.
provinceRank
Indicates the relative position or level assigned to a province within an ordered ranking or hierarchy.
- 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_69d8b9175fec8190af865699b4e64d8c |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e50ed146fc819092b08cb91defb03b |
completed | April 19, 2026, 5:20 p.m. |
| PD | Predicate disambiguation | batch_69e44fe91bc08190906518e1b120fcf0 |
completed | April 19, 2026, 3:45 a.m. |
Created at: April 10, 2026, 10:37 a.m.