Triple
T36320288
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maximal Marginal Relevance |
E894311
|
entity |
| Predicate | typicalSimilarityMeasure |
P57967
|
FINISHED |
| Object | cosine similarity |
—
|
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: cosine similarity | Statement: [Maximal Marginal Relevance, typicalSimilarityMeasure, cosine similarity]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalSimilarityMeasure Context triple: [Maximal Marginal Relevance, typicalSimilarityMeasure, cosine similarity]
-
A.
hasSimilarityTo
Indicates that one entity shares common characteristics, features, or qualities with another entity to a notable degree.
-
B.
namedForSimilarityTo
Indicates that one entity is given its name because of a perceived resemblance or likeness to another entity.
-
C.
distanceMetric
Indicates a quantitative measure of how far apart two entities are within a given space or according to a specified metric.
-
D.
typicalMatchType
Indicates the usual or most common type of match or pairing that characterizes how two entities are related or aligned.
-
E.
typicalMeasure
chosen
Indicates the standard or characteristic quantitative measure typically associated with something, such as its usual size, weight, duration, or other magnitude.
- 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_69f76e4d1a788190a6ab6ccca28547a7 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_6a037c8d06cc8190ab6a5e18d9d2571e |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a0a54cc8190868c1bfa1590d1a6 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:09 p.m.