Triple
T27133634
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Borel set |
E681623
|
entity |
| Predicate | onRealLineForms |
P161881
|
FINISHED |
| Object | Borel σ-algebra on ℝ |
—
|
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: Borel σ-algebra on ℝ | Statement: [Borel set, onRealLineForms, Borel σ-algebra on ℝ]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: onRealLineForms Context triple: [Borel set, onRealLineForms, Borel σ-algebra on ℝ]
-
A.
formedLine
Indicates that an entity has arranged itself or others into a line or linear formation.
-
B.
hasRealFormOf
Indicates that one entity is the concrete, real-world manifestation or physical form of another, more abstract or conceptual entity.
-
C.
formerLine
Indicates that an entity previously served as a particular transit or service line but no longer does so.
-
D.
hasRealForm
Indicates that an abstract, conceptual, or non-physical entity is associated with a concrete, physical manifestation or embodiment.
-
E.
formsPartOfLine
Indicates that one element constitutes a segment or component belonging to a larger line.
- 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_69eefacbcc2081909ebf00daa23f1981 |
completed | April 27, 2026, 5:57 a.m. |
| NER | Named-entity recognition | batch_69f62478fd0c81909b7de1d72aa0e2c0 |
completed | May 2, 2026, 4:21 p.m. |
| PD | Predicate disambiguation | batch_69f61b40f02081909bd9c3ea73249163 |
completed | May 2, 2026, 3:41 p.m. |
| PDg | Predicate description generation | batch_69f61fa35ac48190890102c348ed81a0 |
completed | May 2, 2026, 4 p.m. |
Created at: April 27, 2026, 9:05 a.m.