Triple
T19992657
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | APOE ε3 allele |
E494101
|
entity |
| Predicate | hasApproximateEastAsianFrequency |
P138244
|
FINISHED |
| Object | 0.85 |
—
|
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: 0.85 | Statement: [APOE ε3 allele, hasApproximateEastAsianFrequency, 0.85]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasApproximateEastAsianFrequency Context triple: [APOE ε3 allele, hasApproximateEastAsianFrequency, 0.85]
-
A.
hasStrokeCountApprox
Indicates an approximate number of strokes associated with writing or drawing the related entity.
-
B.
isMostWidelyUsedWritingSystem
Indicates that the subject writing system is used by more people or in more contexts than any other writing system.
-
C.
usesHanjaVariants
Indicates that one entity employs or incorporates alternative Hanja (Chinese character) forms corresponding to another entity.
-
D.
hasMultipleChineseCharacters
Indicates that the referenced item consists of more than one Chinese character.
-
E.
hasApproximateNumberOfLanguages
Indicates that an entity is associated with a quantity representing an estimated or non-exact count of languages.
- F. None of above. chosen
Provenance (4 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_69da626a67648190af9653832a3aeced |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e65fe10ffc81908c94168b0a8ea9c9 |
completed | April 20, 2026, 5:18 p.m. |
| PD | Predicate disambiguation | batch_69e537fd311881908448f2aea8b4812e |
completed | April 19, 2026, 8:15 p.m. |
| PDg | Predicate description generation | batch_69e543c42c688190a22f4d31ec692377 |
completed | April 19, 2026, 9:06 p.m. |
Created at: April 11, 2026, 3:31 p.m.