Triple
T29924735
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Louise Arner Boyd’s European expeditions |
E760045
|
entity |
| Predicate | hasLanguageOfFieldNotes |
P56088
|
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: [Louise Arner Boyd’s European expeditions, hasLanguageOfFieldNotes, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLanguageOfFieldNotes Context triple: [Louise Arner Boyd’s European expeditions, hasLanguageOfFieldNotes, English]
-
A.
hasISO639Note
Indicates that there is an associated note or comment specifically about the ISO 639 language code information for an entity.
-
B.
hasTranslationNote
Indicates that there is an explanatory note about how something has been translated, such as clarifying wording choices, alternatives, or translation issues.
-
C.
hasLinguisticDocumentation
Indicates that there exists recorded linguistic information or documentation about the language or linguistic properties of the subject.
-
D.
hasLanguageUsageNote
Indicates that there is an associated note describing specific usage guidance, nuances, or restrictions for a language element.
-
E.
primaryLanguageOnNotes
chosen
Indicates the main language used in the written notes associated with an entity or resource.
- 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_69f224631674819080c8d089674f9f4f |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69fd783fed9c81909e792702636c4f1f |
completed | May 8, 2026, 5:44 a.m. |
| PD | Predicate disambiguation | batch_69fd7788e63c81909de22fdafcfe41c0 |
completed | May 8, 2026, 5:41 a.m. |
Created at: April 29, 2026, 6:15 p.m.