Triple
T10773126
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grothendieck topology |
E254130
|
entity |
| Predicate | hasKeyNotion |
P95389
|
FINISHED |
| Object | covering sieve |
—
|
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: covering sieve | Statement: [Grothendieck topology, hasKeyNotion, covering sieve]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasKeyNotion Context triple: [Grothendieck topology, hasKeyNotion, covering sieve]
-
A.
notableKey
Indicates that the referenced key is of particular importance or prominence compared to other keys in the same context.
-
B.
hasKeyWork
Indicates that an entity possesses or is associated with a primary or central work (such as a main publication, artwork, or project) that is especially representative or important.
-
C.
hasKeyTheorem
Indicates that one entity contains, relies on, or is characterized by a central or foundational theorem associated with the other entity.
-
D.
hasNotabilityNote
Indicates that there is an associated note or annotation explaining the significance, prominence, or special relevance of the subject.
-
E.
usesNotion
Indicates that one entity makes use of the Notion application or platform for its activities or purposes.
- 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.