Triple
T27254802
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lusternik–Schnirelmann category |
E687582
|
entity |
| Predicate | hasInequality |
P105609
|
FINISHED |
| Object | cat(X) ≥ cup-length(X) + 1 |
—
|
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: cat(X) ≥ cup-length(X) + 1 | Statement: [Lusternik–Schnirelmann category, hasInequality, cat(X) ≥ cup-length(X) + 1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasInequality Context triple: [Lusternik–Schnirelmann category, hasInequality, cat(X) ≥ cup-length(X) + 1]
-
A.
satisfiesInequality
chosen
Indicates that one quantity or expression fulfills the condition specified by a given inequality relation (such as <, ≤, >, or ≥).
-
B.
inequality
Indicates that there is a difference or lack of equality in status, rights, opportunities, or treatment between entities.
-
C.
equalityCondition
Indicates that two values, expressions, or attributes must be exactly the same for the condition to be satisfied.
-
D.
hasInequalityNamedAfter
Indicates that an inequality is named after a particular person or entity.
-
E.
relatedInequality
Indicates that there exists some form of inequality-based relationship or comparison between the entities.
- 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_69ef35567e808190a94458cd44ebff0c |
completed | April 27, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69fd19f791f48190bbb6f6047f9ddc59 |
completed | May 7, 2026, 11:02 p.m. |
| PD | Predicate disambiguation | batch_69fd0df365948190bc9bfc7ffd46acd8 |
completed | May 7, 2026, 10:10 p.m. |
Created at: April 27, 2026, 10:48 a.m.