Triple
T23347127
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | buckminsterfullerene |
E591897
|
entity |
| Predicate | numberOfCarbonAtoms |
P151963
|
FINISHED |
| Object | 60 |
—
|
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: 60 | Statement: [buckminsterfullerene, numberOfCarbonAtoms, 60]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfCarbonAtoms Context triple: [buckminsterfullerene, numberOfCarbonAtoms, 60]
-
A.
hasTypicalCarbonContentRange
Indicates the usual lower and upper bounds of carbon content typically found in or associated with an entity.
-
B.
numberOfCarburetors
Indicates the quantity of carburetors associated with a given entity.
-
C.
numberOfGasCells
Indicates the quantity of distinct gas cells associated with or contained within a given entity or system.
-
D.
electronCount
Indicates the number of electrons associated with a given entity (such as an atom, ion, or molecule) in the described context.
-
E.
hasCarbonToNitrogenRatio
Indicates the proportional relationship between the amount of carbon and the amount of nitrogen present in or associated with an entity.
- F. None of above. chosen
Provenance (4 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_69e25d20e3d08190bcede87673cafb25 |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f19837874481908f1a530261a34819 |
completed | April 29, 2026, 5:33 a.m. |
| PD | Predicate disambiguation | batch_69effcfd8d288190937a887fe6023c11 |
completed | April 28, 2026, 12:19 a.m. |
| PDg | Predicate description generation | batch_69f01d88b4ec8190a2a17a88e0eda178 |
completed | April 28, 2026, 2:38 a.m. |
Created at: April 17, 2026, 5:19 p.m.