Triple
T37328792
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Packing and Covering |
E926681
|
entity |
| Predicate | hasMathematicsSubject |
P196898
|
FINISHED |
| Object | sphere packing |
—
|
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: sphere packing | Statement: [Packing and Covering, hasMathematicsSubject, sphere packing]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMathematicsSubject Context triple: [Packing and Covering, hasMathematicsSubject, sphere packing]
-
A.
hasMathematicalDiscipline
Indicates that one entity is associated with or characterized by a particular branch or field of mathematics.
-
B.
hasMathematicalTopic
chosen
Indicates that one entity is associated with, involves, or is about a particular mathematical topic represented by the other entity.
-
C.
hasMathematicalInterest
Indicates that one entity has an interest in, curiosity about, or engagement with mathematics in relation to another entity or mathematical subject.
-
D.
hasMatha
Indicates a relationship where one entity possesses, is associated with, or is characterized by a specific matha (monastic institution or religious seat).
-
E.
supportsMathematicsTopic
Indicates that one entity provides assistance, resources, or reinforcement for understanding or working with a particular mathematics topic.
- 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_69f76eb386d88190a8d511aa11540dfc |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_6a037c8efcd4819088c2aeead65d93df |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a13a1308190a202df66f4781855 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:16 p.m.