Triple
T5425467
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sperner's lemma |
E121351
|
entity |
| Predicate | labelingRule |
P63670
|
FINISHED |
| Object | vertices on a face may only use labels of that face |
—
|
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: vertices on a face may only use labels of that face | Statement: [Sperner's lemma, labelingRule, vertices on a face may only use labels of that face]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: labelingRule Context triple: [Sperner's lemma, labelingRule, vertices on a face may only use labels of that face]
-
A.
labelOf
Indicates that one entity serves as the name, tag, or identifying label assigned to another entity.
-
B.
notableRule
Indicates that a rule or regulation is particularly significant, prominent, or noteworthy within a given context.
-
C.
compositionRule
Indicates how multiple elements or components are combined or arranged according to a specific rule or pattern.
-
D.
labelCatalog
Indicates assigning or associating a descriptive label or identifier with a catalog entity or catalog entry.
-
E.
styleOfRule
Indicates the stylistic or formatting convention that a particular rule follows or is expressed in.
- 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_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. |
| PDg | Predicate description generation | batch_69bd8910de688190aa0cd80627849a60 |
completed | March 20, 2026, 5:51 p.m. |
Created at: March 20, 2026, 2:06 p.m.