Triple
T21288958
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wergaia people |
E524735
|
entity |
| Predicate | hasLinguisticConnectionTo |
P87230
|
FINISHED |
| Object | Country |
—
|
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: Country | Statement: [Wergaia people, hasLinguisticConnectionTo, Country]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLinguisticConnectionTo Context triple: [Wergaia people, hasLinguisticConnectionTo, Country]
-
A.
linguisticallyRelatedTo
Indicates that two entities are connected through a linguistic relationship, such as sharing a common language, origin, structure, or other language-based association.
-
B.
hasLexicalInfluenceOn
Indicates that one linguistic element (such as a word, phrase, or lexicon) has affected or shaped the form, usage, or meaning of another linguistic element.
-
C.
hasCommonLoanwordsFrom
Indicates that two languages share loanwords that originate from the same source language.
-
D.
cognateOf
Indicates that two linguistic forms share a common historical origin, typically descending from the same ancestral word.
-
E.
linkedToLanguage
chosen
Indicates that an entity has an association or connection with a specific language, such as being expressed in, related to, or dependent on that 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_69e0b5171f6c8190a5d57201ede73811 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e736d882408190a2300327cb73b7f6 |
completed | April 21, 2026, 8:35 a.m. |
| PD | Predicate disambiguation | batch_69e61612ab748190a72b8703b938abcb |
completed | April 20, 2026, 12:03 p.m. |
Created at: April 16, 2026, 4:03 p.m.