Triple
T1078897
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Old Frisian |
E23900
|
entity |
| Predicate | lexicalSimilarity |
P11829
|
FINISHED |
| Object | high with Old 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: high with Old English | Statement: [Old Frisian, lexicalSimilarity, high with Old English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lexicalSimilarity Context triple: [Old Frisian, lexicalSimilarity, high with Old English]
-
A.
hasLexicalSimilarityWith
chosen
Indicates that two linguistic items share a significant degree of similarity in form, structure, or wording.
-
B.
hasGrammaticalSimilarityTo
Indicates that two linguistic elements share similar grammatical structure, form, or function.
-
C.
hasPhonologicalSimilarityTo
Indicates that two linguistic elements share similar sound patterns or phonological features.
-
D.
linguisticallyRelatedTo
Indicates that two entities are connected through a linguistic relationship, such as sharing a common language, origin, structure, or other language-based association.
-
E.
synonym
Indicates that two terms have the same or nearly the same meaning in a given context.
- 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_69a493f1ddf48190a99d54b00e99f8ce |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b943b41481909b24050ca7e78971 |
completed | March 1, 2026, 10:10 p.m. |
| PD | Predicate disambiguation | batch_69a4b73d9f08819093668104f129840e |
completed | March 1, 2026, 10:01 p.m. |
Created at: March 1, 2026, 7:42 p.m.