Triple
T10773193
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grothendieck group |
E254131
|
entity |
| Predicate | hasCanonicalMapFrom |
P95390
|
FINISHED |
| Object | underlying commutative monoid |
—
|
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: underlying commutative monoid | Statement: [Grothendieck group, hasCanonicalMapFrom, underlying commutative monoid]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCanonicalMapFrom Context triple: [Grothendieck group, hasCanonicalMapFrom, underlying commutative monoid]
-
A.
hasCanonicalRepresentation
Indicates that one entity is the standard or authoritative form in which another entity is represented.
-
B.
hasCanonicalReference
Indicates that one entity serves as the authoritative or standard reference source for another entity.
-
C.
hasCanonicalAspect
Indicates that an entity is associated with its standard or officially recognized aspect, form, or representation.
-
D.
hasMapReference
Indicates that an entity is associated with a specific map or map location reference.
-
E.
hasCanonicalTerm
Indicates that one term in a set is designated as the standard or authoritative form used to represent a concept or 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_69d6aa5f54f4819082d0bbcb6f8797e6 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d7329b27748190bd0e2569c7972fd1 |
completed | April 9, 2026, 5:01 a.m. |
| PD | Predicate disambiguation | batch_69d6f31455648190b5c24690487b1b54 |
completed | April 9, 2026, 12:30 a.m. |
| PDg | Predicate description generation | batch_69d6fa334b8c819082eaf8537084c323 |
completed | April 9, 2026, 1 a.m. |
Created at: April 8, 2026, 9:16 p.m.