Triple
T26646508
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Daizy |
E668927
|
entity |
| Predicate | hasPronunciationSimilarityTo |
P8038
|
FINISHED |
| Object | Daisy |
—
|
NE NERFINISHED |
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: Daisy | Statement: [Daizy, hasPronunciationSimilarityTo, Daisy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPronunciationSimilarityTo Context triple: [Daizy, hasPronunciationSimilarityTo, Daisy]
-
A.
hasPhonologicalSimilarityTo
chosen
Indicates that two linguistic elements share similar sound patterns or phonological features.
-
B.
hasPronunciationDifferenceFrom
Indicates that two linguistic items differ in how they are pronounced.
-
C.
hasGrammaticalSimilarityTo
Indicates that two linguistic elements share similar grammatical structure, form, or function.
-
D.
hasLanguageSimilarTo
Indicates that one entity uses or is associated with a language that is similar or closely related to the language used or associated with another entity.
-
E.
hasLexicalSimilarityWith
Indicates that two linguistic items share a significant degree of similarity in form, structure, or wording.
- 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_69ee9d00eb5481908d6c6d0ada2f0c9a |
completed | April 26, 2026, 11:17 p.m. |
| NER | Named-entity recognition | batch_69fd37b695c88190855801626f91c4cd |
completed | May 8, 2026, 1:09 a.m. |
| PD | Predicate disambiguation | batch_69fd374cccf08190a230e87164af5938 |
completed | May 8, 2026, 1:07 a.m. |
Created at: April 27, 2026, 2:31 a.m.