Triple
T11057972
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 3DISCO tissue clearing method |
E261427
|
entity |
| Predicate | usesReagent |
P25490
|
FINISHED |
| Object | tetrahydrofuran |
—
|
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: tetrahydrofuran | Statement: [3DISCO tissue clearing method, usesReagent, tetrahydrofuran]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesReagent Context triple: [3DISCO tissue clearing method, usesReagent, tetrahydrofuran]
-
A.
containsSpeciesUsedAs
Indicates that something includes, as part of its composition or content, a particular species that is used for a specified purpose.
-
B.
hasResearchUse
Indicates that an entity is used for, or associated with, conducting research activities or purposes.
-
C.
usedWith
Indicates that one entity is typically or appropriately employed together with another entity in a combined or complementary use.
-
D.
usedAgainst
Indicates that one entity is employed, applied, or deployed in opposition to, or for the purpose of affecting, another entity.
-
E.
areUsedIn
chosen
Indicates that certain entities serve as components, tools, or resources within a particular process, context, or application.
- 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_69d6aa98650481908609c7c56bfa7902 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d798a2efa48190b290f43dfe836501 |
completed | April 9, 2026, 12:16 p.m. |
| PD | Predicate disambiguation | batch_69d7440da46c8190a77380d5d747ac9c |
completed | April 9, 2026, 6:15 a.m. |
Created at: April 8, 2026, 9:26 p.m.