Triple
T8278399
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zinin reduction |
E193604
|
entity |
| Predicate | reagentType |
P16615
|
FINISHED |
| Object | sulfide-based reducing agents |
—
|
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: sulfide-based reducing agents | Statement: [Zinin reduction, reagentType, sulfide-based reducing agents]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: reagentType Context triple: [Zinin reduction, reagentType, sulfide-based reducing agents]
-
A.
reactorType
Indicates the specific kind or category of reactor associated with an entity.
-
B.
substanceType
chosen
Indicates the specific kind or category of substance associated with an entity or relation.
-
C.
reactant
Indicates that an entity participates as a starting material or input substance in a chemical or reactive process.
-
D.
reactionType
Indicates the specific kind or category of reaction that occurs between entities or in response to an event or stimulus.
-
E.
typeOfRemedy
Indicates that one entity is a specific kind or category of remedy in relation to another 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_69ca82e217a48190880695635c44b2ed |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb79ebb6b88190bc777b8bd72fcdbc |
completed | March 31, 2026, 7:38 a.m. |
| PD | Predicate disambiguation | batch_69cb70a4525481909399d313a6247ace |
completed | March 31, 2026, 6:58 a.m. |
Created at: March 30, 2026, 5:51 p.m.