Triple
T26134127
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | St. Catharine plantation, Charles County, Maryland |
E659328
|
entity |
| Predicate | languageOfLocalRecords |
P876
|
FINISHED |
| Object | English |
—
|
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: English | Statement: [St. Catharine plantation, Charles County, Maryland, languageOfLocalRecords, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfLocalRecords Context triple: [St. Catharine plantation, Charles County, Maryland, languageOfLocalRecords, English]
-
A.
languageOfRecords
chosen
Indicates the language in which the records are written or maintained.
-
B.
languageOfLocalization
Indicates the language into which something (such as software, content, or an interface) has been localized for use or display.
-
C.
languageUsedInLocality
Indicates that a particular language is used or spoken within a specific locality or geographic area.
-
D.
languageOfLocalOrganization
Indicates the language used or officially adopted by a local organization in its operations or communications.
-
E.
languageOfSources
Indicates that the specified language is the language in which the referenced sources or source materials are expressed.
- 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_69ee5bc3c20c8190bf2cf272f4170e95 |
completed | April 26, 2026, 6:38 p.m. |
| NER | Named-entity recognition | batch_69f79f48acec8190a9d5964581a94f6c |
completed | May 3, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_69f79e4888248190be2f63cdfb5cd7b7 |
completed | May 3, 2026, 7:13 p.m. |
Created at: April 26, 2026, 8:16 p.m.