Triple
T38125072
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dawnna |
E952043
|
entity |
| Predicate | phoneticSimilarityTo |
P8038
|
FINISHED |
| Object | Donna |
—
|
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: Donna | Statement: [Dawnna, phoneticSimilarityTo, Donna]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: phoneticSimilarityTo Context triple: [Dawnna, phoneticSimilarityTo, Donna]
-
A.
hasPhonologicalSimilarityTo
chosen
Indicates that two linguistic elements share similar sound patterns or phonological features.
-
B.
hasLetterSetSimilarity
Indicates that two entities share a similar set of letters, typically based on overlap or resemblance between the characters in their textual representations.
-
C.
hasSimilarityTo
Indicates that one entity shares common characteristics, features, or qualities with another entity to a notable degree.
-
D.
isPhonetic
Indicates that one entity represents the phonetic (sound-based) form or pronunciation of another entity.
-
E.
phoneticLength
Indicates the relationship between an expression and the duration or number of phonetic units (such as sounds or syllables) required to pronounce it.
- 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_69f76f083548819082bd2bbf53c79e8e |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fc4748843c8190931432653be4890c |
completed | May 7, 2026, 8:03 a.m. |
| PD | Predicate disambiguation | batch_69fc45646ce481908caf292ff9f06e15 |
completed | May 7, 2026, 7:55 a.m. |
Created at: May 3, 2026, 4:21 p.m.