Triple
T33841157
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | arachidonic acid |
E867360
|
entity |
| Predicate | carbonAtoms |
P151963
|
FINISHED |
| Object | 20 |
—
|
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: 20 | Statement: [arachidonic acid, carbonAtoms, 20]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: carbonAtoms Context triple: [arachidonic acid, carbonAtoms, 20]
-
A.
numberOfCarbonAtoms
chosen
Indicates the count of carbon atoms present in a specified chemical entity or structure.
-
B.
hasCarbonHybridization
Indicates the specific type of carbon atom hybridization (e.g., sp, sp2, sp3) associated with an entity in a molecular or chemical context.
-
C.
carbonContent
Indicates the amount or proportion of carbon present in a given substance, material, or entity.
-
D.
electronCount
Indicates the number of electrons associated with a given entity (such as an atom, ion, or molecule) in the described context.
-
E.
hasTypicalCarbonContentRange
Indicates the usual lower and upper bounds of carbon content typically found in or associated with an 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_69f34992ad40819087760ed939bd2a7a |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f7004f4d9c8190b6517493f08084d4 |
completed | May 3, 2026, 7:59 a.m. |
| PD | Predicate disambiguation | batch_69f6fc59518081908b0275f47721d561 |
completed | May 3, 2026, 7:42 a.m. |
Created at: May 1, 2026, 1:47 a.m.