Triple
T36599643
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MS4A1 |
E902882
|
entity |
| Predicate | hasTransmembraneDomainCount |
P39646
|
FINISHED |
| Object | 4 |
—
|
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: 4 | Statement: [MS4A1, hasTransmembraneDomainCount, 4]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTransmembraneDomainCount Context triple: [MS4A1, hasTransmembraneDomainCount, 4]
-
A.
hasTransmembraneDomains
chosen
Indicates that an entity (typically a protein) possesses one or more regions that span across a biological membrane.
-
B.
estimatedNumberOfGenes
Indicates the approximate count of genes that an entity (such as an organism or genome) is believed to possess.
-
C.
hasOuterMembrane
Indicates that an entity possesses an outer membrane surrounding its main cellular or structural body.
-
D.
membraneType
Indicates the specific kind or classification of membrane associated with an entity.
-
E.
exonCountApproximate
Indicates that the number of exons associated with an entity is an estimated or approximate count rather than an exact value.
- 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_69f76e66b7b88190848f7a3e1188915f |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69fff86e544c81908063f61b876c9d78 |
completed | May 10, 2026, 3:15 a.m. |
| PD | Predicate disambiguation | batch_69fff7e7cb688190977eeca41aad25b9 |
completed | May 10, 2026, 3:13 a.m. |
Created at: May 3, 2026, 4:11 p.m.