Triple
T5625437
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sardinian Sassarese dialect |
E147705
|
entity |
| Predicate | hasLexiconSimilarTo |
P11829
|
FINISHED |
| Object | Corsican language |
—
|
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: Corsican language | Statement: [Sardinian Sassarese dialect, hasLexiconSimilarTo, Corsican language]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLexiconSimilarTo Context triple: [Sardinian Sassarese dialect, hasLexiconSimilarTo, Corsican language]
-
A.
hasLexicalSimilarityWith
chosen
Indicates that two linguistic items share a significant degree of similarity in form, structure, or wording.
-
B.
hasPhonologicalSimilarityTo
Indicates that two linguistic elements share similar sound patterns or phonological features.
-
C.
hasGrammaticalSimilarityTo
Indicates that two linguistic elements share similar grammatical structure, form, or function.
-
D.
hasLetterSetSimilarity
Indicates that two entities share a similar set of letters, typically based on overlap or resemblance between the characters in their textual representations.
-
E.
hasCommonLoanwordsFrom
Indicates that two languages share loanwords that originate from the same source 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_69c00906f2a88190a992c66b13d606d4 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c02235b4e48190a529f70605bf47ca |
completed | March 22, 2026, 5:09 p.m. |
| PD | Predicate disambiguation | batch_69c01b1d4b108190846ce586dc783acf |
completed | March 22, 2026, 4:38 p.m. |
Created at: March 22, 2026, 3:40 p.m.