Triple
T27176288
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lévy–Prokhorov metric |
E683051
|
entity |
| Predicate | metrizes |
P161937
|
FINISHED |
| Object | weak convergence of probability measures |
—
|
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: weak convergence of probability measures | Statement: [Lévy–Prokhorov metric, metrizes, weak convergence of probability measures]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: metrizes Context triple: [Lévy–Prokhorov metric, metrizes, weak convergence of probability measures]
-
A.
meter
Indicates a measurement relationship where one entity quantifies the length, distance, or extent of another in meters.
-
B.
metre
Indicates a measurement relationship where one entity’s length, distance, or size is quantified in units of metres.
-
C.
mètre
Indicates a measurement relationship where one entity serves as the unit "meter" used to quantify the length, distance, or size of another entity.
-
D.
מטרה
Indicates that an entity serves as the goal, aim, or intended target of another entity or action.
-
E.
metricForm
Indicates that one entity is expressed or represented in a particular metric form or measurement format relative to another.
- 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_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_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, 9:26 a.m.