Triple
T11792662
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stafford County, Colony of Virginia |
E280424
|
entity |
| Predicate | hadPrimaryLanguage |
P93029
|
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: [Stafford County, Colony of Virginia, hadPrimaryLanguage, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hadPrimaryLanguage Context triple: [Stafford County, Colony of Virginia, hadPrimaryLanguage, English]
-
A.
hasPrimaryLanguage1
Indicates that an entity’s main or most commonly used language is the specified language.
-
B.
primaryLanguageOf
Indicates that a specified language is the main or official language used by a particular entity (such as a person, organization, or region).
-
C.
primaryLanguageIn
chosen
Indicates that a specified language is the main or official language used within a particular place, organization, or context.
-
D.
primaryLanguageHeritage
Indicates that one language is the main ancestral or culturally inherited language associated with an entity.
-
E.
hasSecondaryLanguage
Indicates that an entity possesses or uses a secondary language in addition to its primary language.
- 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_69d6ab258b808190b1735835c841e3a4 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8a588d2c881909783c2d678c2a474 |
completed | April 10, 2026, 7:23 a.m. |
| PD | Predicate disambiguation | batch_69d8a2491f048190853239bc05090bf4 |
completed | April 10, 2026, 7:10 a.m. |
Created at: April 8, 2026, 9:42 p.m.