Triple
T4123916
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fernando Po Krio |
E92677
|
entity |
| Predicate | primaryLexicalSource |
P3083
|
FINISHED |
| Object | English vocabulary |
—
|
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 vocabulary | Statement: [Fernando Po Krio, primaryLexicalSource, English vocabulary]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryLexicalSource Context triple: [Fernando Po Krio, primaryLexicalSource, English vocabulary]
-
A.
primaryLexifierLanguage
chosen
Indicates the main source language from which the core vocabulary and structure of another language, typically a contact or creole language, are primarily derived.
-
B.
primaryCorpusType
Indicates the main or dominant type or category of corpus associated with an entity.
-
C.
primarySources
Indicates that one entity serves as an original, authoritative source of information or evidence for another entity.
-
D.
primaryLanguageOf
Indicates that a specified language is the main or official language used by a particular entity (such as a person, organization, or region).
-
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_69aed9685f70819086932777aec8d959 |
completed | March 9, 2026, 2:30 p.m. |
| NER | Named-entity recognition | batch_69af0246e40081908ad6741a830ca68e |
completed | March 9, 2026, 5:24 p.m. |
| PD | Predicate disambiguation | batch_69af01867698819098e4144634b2ec4f |
completed | March 9, 2026, 5:21 p.m. |
Created at: March 9, 2026, 3:41 p.m.