Triple
T23500238
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Martin County, Florida |
E571818
|
entity |
| Predicate | hasCountyNumberInFlorida |
P152620
|
FINISHED |
| Object | 43 |
—
|
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: 43 | Statement: [Martin County, Florida, hasCountyNumberInFlorida, 43]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCountyNumberInFlorida Context triple: [Martin County, Florida, hasCountyNumberInFlorida, 43]
-
A.
hasCountyNumberInIndiana
Indicates that a county is associated with its designated county number within the state of Indiana.
-
B.
hasCountyCode
Indicates that an entity is associated with a specific county identified by a standardized county code.
-
C.
hasCountyNumberInKansas
Indicates that an entity is assigned a specific official county number within the state of Kansas.
-
D.
hasCountyCodeType
Indicates that an entity is associated with a specific type or classification of county code.
-
E.
hasCountyNumberInKentucky
Indicates that a county is assigned a specific official county number within the state of Kentucky.
- 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_69e245b4829881909b77a70e942bbd54 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1a8fc37908190af86a01ab85737d6 |
completed | April 29, 2026, 6:45 a.m. |
| PD | Predicate disambiguation | batch_69f0621165c08190a0b27b1319733959 |
completed | April 28, 2026, 7:30 a.m. |
| PDg | Predicate description generation | batch_69f0bd4a0e408190ad8916faf23562d9 |
completed | April 28, 2026, 1:59 p.m. |
Created at: April 17, 2026, 6:06 p.m.