Triple
T27176289
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lévy–Prokhorov metric |
E683051
|
entity |
| Predicate | metrizes |
P161937
|
FINISHED |
| Object | convergence in distribution |
—
|
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: convergence in distribution | Statement: [Lévy–Prokhorov metric, metrizes, convergence in distribution]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: metrizes Context triple: [Lévy–Prokhorov metric, metrizes, convergence in distribution]
-
A.
metrizes
chosen
Indicates that a given metric defines or induces the topology or structure on a space, making that metric compatible with and fully characterizing the space’s topological properties.
-
B.
meter
Indicates a measurement relationship where one entity quantifies the length, distance, or extent of another in meters.
-
C.
metre
Indicates a measurement relationship where one entity’s length, distance, or size is quantified in units of metres.
-
D.
mètre
Indicates a measurement relationship where one entity serves as the unit "meter" used to quantify the length, distance, or size of another entity.
-
E.
מטרה
Indicates that an entity serves as the goal, aim, or intended target of another entity or action.
- 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_69eefad086808190ab89816c0c300476 |
completed | April 27, 2026, 5:57 a.m. |
| NER | Named-entity recognition | batch_69f6257a5ae881908db3032511378836 |
completed | May 2, 2026, 4:25 p.m. |
| PD | Predicate disambiguation | batch_69f620e38aec8190bb184edcdbd6da64 |
completed | May 2, 2026, 4:05 p.m. |
Created at: April 27, 2026, 9:26 a.m.