Triple
T6318194
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jayme |
E141666
|
entity |
| Predicate | typicalPronunciationLanguage |
P27691
|
FINISHED |
| Object | 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: English | Statement: [Jayme, typicalPronunciationLanguage, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalPronunciationLanguage Context triple: [Jayme, typicalPronunciationLanguage, English]
-
A.
pronunciationLanguage
chosen
Indicates the language in which the pronunciation of an entity (such as a word or name) is given.
-
B.
typicalLanguages
Indicates the languages that are commonly or characteristically used, spoken, or associated with a given entity.
-
C.
hasStandardPronunciationBasedOn
Indicates that one entity’s standard or canonical pronunciation is determined or derived from another entity’s pronunciation.
-
D.
isSpokenAs
Indicates that one entity is used as the spoken or verbal form of another entity (e.g., a word, name, or phrase).
-
E.
typicalLanguageOfReadings
Indicates the language that is most commonly used for readings or interpretations associated with a given entity.
- 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_69c008d13b8c8190be47d896eb735605 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c064c38fe48190a71a4e5e1af19b10 |
completed | March 22, 2026, 9:53 p.m. |
| PD | Predicate disambiguation | batch_69c060e5efc48190861b8266e5b0cc0c |
completed | March 22, 2026, 9:36 p.m. |
Created at: March 22, 2026, 4:29 p.m.