Triple
T36491713
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Relation Networks for few-shot learning |
E899065
|
entity |
| Predicate | relationScoreRange |
P204898
|
FINISHED |
| Object | [0,1] similarity score |
—
|
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: [0,1] similarity score | Statement: [Relation Networks for few-shot learning, relationScoreRange, [0,1] similarity score]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationScoreRange Context triple: [Relation Networks for few-shot learning, relationScoreRange, [0,1] similarity score]
-
A.
rankingPointsRange
Indicates the range of ranking points assigned or applicable to an entity within a ranking or scoring system.
-
B.
relationshipReputation
Indicates how one entity’s standing, trustworthiness, or esteem is perceived by another entity or within a given context.
-
C.
relationshipScope
Indicates the contextual boundaries or extent within which a particular relationship between entities is defined or considered valid.
-
D.
relationshipImpact
Indicates how one entity’s relationship with another affects or changes those entities or their interaction.
-
E.
coScoredWith
Indicates that two or more entities received the same score or were evaluated with an identical scoring outcome in a shared context.
- 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_69f76e5ad4588190bdbce60c52fbb785 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_6a037c92f03c8190ae2751270b195423 |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a0bf4b88190bdcfae9a14b51f0a |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c82f8c88190bd77a086023ac0e1 |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 3, 2026, 4:10 p.m.