Triple
T34471531
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Montel space |
E884920
|
entity |
| Predicate | hasDefiningProperty |
P23698
|
FINISHED |
| Object | every closed and bounded subset is compact |
—
|
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: every closed and bounded subset is compact | Statement: [Montel space, hasDefiningProperty, every closed and bounded subset is compact]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDefiningProperty Context triple: [Montel space, hasDefiningProperty, every closed and bounded subset is compact]
-
A.
hasDefiningGroup
Indicates that an entity is characterized or identified by belonging to a particular group that defines its nature, role, or classification.
-
B.
hasDefinition
Indicates that one entity provides the meaning, explanation, or definition of another entity.
-
C.
haveProperty
chosen
Indicates that an entity possesses, exhibits, or is characterized by a particular property or attribute.
-
D.
hasPrototype
Indicates that an entity is based on, derived from, or exemplified by a specific prototype.
-
E.
hasAncestralProperty
Indicates that an entity possesses a property, trait, or characteristic that originates from or is inherited through its ancestors.
- 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_69f349c880408190ade571c471ab154a |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69ff1e3e13c08190bb8990c44716b746 |
completed | May 9, 2026, 11:45 a.m. |
| PD | Predicate disambiguation | batch_69ff1dfcaf2c8190aaf2b428d57b7782 |
completed | May 9, 2026, 11:43 a.m. |
Created at: May 1, 2026, 2:01 a.m.