Triple
T7803624
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fischer esterification |
E180491
|
entity |
| Predicate | leChatelierPrincipleApplied |
P1757
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Fischer esterification, leChatelierPrincipleApplied, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: leChatelierPrincipleApplied Context triple: [Fischer esterification, leChatelierPrincipleApplied, true]
-
A.
keyChemicalDiscussed
Indicates that a particular chemical substance is a central topic of discussion in a given context or communication.
-
B.
usedInChemistry
Indicates that something is employed or applied within the context of chemistry, such as in chemical processes, experiments, or analyses.
-
C.
usesPrinciple
chosen
Indicates that one entity applies, relies on, or is based upon a particular principle in its functioning, reasoning, or design.
-
D.
concentration
Indicates the degree to which a substance or entity is present within a given medium, mixture, or space.
-
E.
appliesTheory
Indicates that an entity uses or implements a particular theory in analyzing, explaining, or addressing something.
- 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_69ca827e50cc8190a92a733577184938 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69caf78a6d88819093f83528fe88b182 |
completed | March 30, 2026, 10:22 p.m. |
| PD | Predicate disambiguation | batch_69cae9111b2481909684a2d4aa4831c2 |
completed | March 30, 2026, 9:20 p.m. |
Created at: March 30, 2026, 4:34 p.m.