Triple
T1911973
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Becky |
E38129
|
entity |
| Predicate | hasIPAPronunciation |
P5704
|
FINISHED |
| Object | /ˈbɛki/ |
—
|
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: /ˈbɛki/ | Statement: [Becky, hasIPAPronunciation, /ˈbɛki/]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasIPAPronunciation Context triple: [Becky, hasIPAPronunciation, /ˈbɛki/]
-
A.
hasIPA
chosen
Indicates that an entity is associated with a specific International Phonetic Alphabet (IPA) transcription representing its pronunciation.
-
B.
hasPronunciationDifferenceFrom
Indicates that two linguistic items differ in how they are pronounced.
-
C.
isPhonetic
Indicates that one entity represents the phonetic (sound-based) form or pronunciation of another entity.
-
D.
hasStandardPronunciationBasedOn
Indicates that one entity’s standard or canonical pronunciation is determined or derived from another entity’s pronunciation.
-
E.
hasPhoneme
Indicates that a linguistic unit (such as a word or morpheme) contains or includes a particular phoneme as part of its sound structure.
- 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_69a8862a26088190aae5243695aeefc0 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb34d94fc8190a5bf1e582c77c725 |
completed | March 7, 2026, 5:10 a.m. |
| PD | Predicate disambiguation | batch_69abafeba3d88190afcce67483d8625b |
completed | March 7, 2026, 4:56 a.m. |
Created at: March 4, 2026, 7:35 p.m.