Triple
T37490449
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yoshinori |
E931668
|
entity |
| Predicate | nameLengthInSyllables |
P6574
|
FINISHED |
| Object | four syllables in Japanese (yo-shi-no-ri) |
—
|
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: four syllables in Japanese (yo-shi-no-ri) | Statement: [Yoshinori, nameLengthInSyllables, four syllables in Japanese (yo-shi-no-ri)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nameLengthInSyllables Context triple: [Yoshinori, nameLengthInSyllables, four syllables in Japanese (yo-shi-no-ri)]
-
A.
hasSyllableCount
chosen
Indicates that one entity (typically a word or phrase) possesses a specific number of syllables given by the other entity.
-
B.
nameLengthInHangulSyllables
Indicates the number of Hangul syllable characters that make up an entity’s name.
-
C.
languageOfSyllables
Indicates a relationship where a language is characterized or defined by the specific set or system of syllables it uses.
-
D.
usesSyllables
Indicates that one entity forms, expresses, or analyzes something by employing syllables as its basic units.
-
E.
numberOfSyllabicSignsApprox
Indicates an approximate count of syllabic signs associated with an 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_69f76ec457a4819094eeb3aed9baac11 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fba68077788190b311e027435fcf87 |
completed | May 6, 2026, 8:37 p.m. |
| PD | Predicate disambiguation | batch_69fba34c65ac8190b298f0f00d1dcc0e |
completed | May 6, 2026, 8:23 p.m. |
Created at: May 3, 2026, 4:17 p.m.