Triple
T5425527
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Euclidean metric |
E121352
|
entity |
| Predicate | hasNormRelation |
P33476
|
FINISHED |
| Object | d(x,y) = ||x - y||2 |
—
|
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: d(x,y) = ||x - y||2 | Statement: [Euclidean metric, hasNormRelation, d(x,y) = ||x - y||2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNormRelation Context triple: [Euclidean metric, hasNormRelation, d(x,y) = ||x - y||2]
-
A.
hasNorm
Indicates that an entity is associated with, governed by, or characterized through a particular norm, rule, or standard.
-
B.
hasRelation
chosen
Indicates that there exists some specified relationship or association between two entities.
-
C.
hasPrimitiveRelation
Indicates a basic, direct relationship between entities that is not derived from or dependent on any other relations.
-
D.
hasNormativeCategory
Indicates that something is associated with a particular normative category, such as a standard, rule, or evaluative classification that prescribes how it ought to be regarded or treated.
-
E.
usesNormalization
Indicates that one entity applies or relies on a normalization process or technique in relation to another entity or data.
- 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_69bd463b58d88190b258261573de9e91 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd8911a7348190ad9378a248190f07 |
completed | March 20, 2026, 5:51 p.m. |
| PD | Predicate disambiguation | batch_69bd846b8bdc81909dcdc2a3084226f2 |
completed | March 20, 2026, 5:31 p.m. |
Created at: March 20, 2026, 2:06 p.m.