Triple
T22692120
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sanger sequencing |
E561076
|
entity |
| Predicate | nowOftenUses |
P108786
|
FINISHED |
| Object | fluorescently labeled dideoxynucleotides |
—
|
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: fluorescently labeled dideoxynucleotides | Statement: [Sanger sequencing, nowOftenUses, fluorescently labeled dideoxynucleotides]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nowOftenUses Context triple: [Sanger sequencing, nowOftenUses, fluorescently labeled dideoxynucleotides]
-
A.
oftenUse
chosen
Indicates that one entity frequently or regularly uses, employs, or utilizes another entity.
-
B.
frequentUseCase
Indicates a situation, scenario, or pattern of use that occurs regularly or more often than others in relation to the subject.
-
C.
usesFrequency
Indicates that one entity employs or operates another entity at a specified rate, interval, or number of occurrences over time.
-
D.
frequentOccasion
Indicates that a particular event, situation, or condition occurs repeatedly or commonly over time.
-
E.
oftenUsedAfter
Indicates that one entity is frequently or typically used immediately following another entity in a sequence or workflow.
- 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_69e2454d71b48190a1f80af9f82b6fcf |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f1789ba0148190891781d05ec64f3c |
completed | April 29, 2026, 3:18 a.m. |
| PD | Predicate disambiguation | batch_69ee62b2259c819091ed1387a748b9f3 |
completed | April 26, 2026, 7:08 p.m. |
Created at: April 17, 2026, 3:13 p.m.