Triple
T26314023
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Monroe County, Ohio |
E661910
|
entity |
| Predicate | hasCountyNumberInOhio |
P194598
|
FINISHED |
| Object | 56 |
—
|
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: 56 | Statement: [Monroe County, Ohio, hasCountyNumberInOhio, 56]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCountyNumberInOhio Context triple: [Monroe County, Ohio, hasCountyNumberInOhio, 56]
-
A.
hasCountyNumberInIndiana
Indicates that a county is associated with its designated county number within the state of Indiana.
-
B.
hasCountyNumberInKansas
Indicates that an entity is assigned a specific official county number within the state of Kansas.
-
C.
hasCountyNumberInKentucky
Indicates that a county is assigned a specific official county number within the state of Kentucky.
-
D.
hasCountyNumberInFlorida
Indicates that a county is associated with a specific official county identification number used within the state of Florida.
-
E.
hasCountyNumberInTennessee
Indicates that an entity is assigned a specific official county number within the state of Tennessee.
- F. None of above. chosen
Provenance (4 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_69ee812dacfc81908484aade9120fba9 |
completed | April 26, 2026, 9:18 p.m. |
| NER | Named-entity recognition | batch_69fd7e364a648190a1e9e1d9fc76e99e |
completed | May 8, 2026, 6:09 a.m. |
| PD | Predicate disambiguation | batch_69fd7bb547608190a3b04dddbca6b8bc |
completed | May 8, 2026, 5:59 a.m. |
| PDg | Predicate description generation | batch_69fd7e35967081909f8bc8389d976ffd |
completed | May 8, 2026, 6:09 a.m. |
Created at: April 26, 2026, 10:23 p.m.