Triple
T6458159
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aldersgate experience |
E142045
|
entity |
| Predicate | hasLanguageOfPrimaryAccount |
P1252
|
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: [Aldersgate experience, hasLanguageOfPrimaryAccount, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLanguageOfPrimaryAccount Context triple: [Aldersgate experience, hasLanguageOfPrimaryAccount, English]
-
A.
hasSecondaryLanguage
Indicates that an entity possesses or uses a secondary language in addition to its primary language.
-
B.
primaryLanguageOf
chosen
Indicates that a specified language is the main or official language used by a particular entity (such as a person, organization, or region).
-
C.
hasLanguageStatus
Indicates that an entity has a particular status or condition regarding its language use, recognition, or classification.
-
D.
hasLanguageOfOrders
Indicates that one entity uses or is associated with a particular language for issuing orders or commands to another entity.
-
E.
isLanguageOf
Indicates that a particular language is used as the official or primary language associated with a given entity (such as a person, document, or region).
- 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_69c008d2f91c8190a8178767a35e08fc |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c069d758508190b9c7358ef84f8169 |
completed | March 22, 2026, 10:14 p.m. |
| PD | Predicate disambiguation | batch_69c0673b44148190aed70084f0ff4992 |
completed | March 22, 2026, 10:03 p.m. |
Created at: March 22, 2026, 4:48 p.m.