Triple
T24806337
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ivar Bendixson |
E620666
|
entity |
| Predicate | hasNameInTheorem |
P29208
|
FINISHED |
| Object | Poincaré–Bendixson theorem |
—
|
NE NERFINISHED |
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: Poincaré–Bendixson theorem | Statement: [Ivar Bendixson, hasNameInTheorem, Poincaré–Bendixson theorem]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNameInTheorem Context triple: [Ivar Bendixson, hasNameInTheorem, Poincaré–Bendixson theorem]
-
A.
hasTheorem
Indicates that one entity (typically a mathematical theory, field, or work) includes, establishes, or is associated with a particular theorem.
-
B.
hasTheoremNamedAfter
chosen
Indicates that a theorem is named in honor of or after a particular person or entity.
-
C.
hasKeyTheorem
Indicates that one entity contains, relies on, or is characterized by a central or foundational theorem associated with the other entity.
-
D.
namedForTheory
Indicates that something is named in honor of, or derived from, a particular theory.
-
E.
hasNameInFormula
Indicates that an entity is referred to by a specific name or symbol within a formula or formal expression.
- 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_69e2fabf26bc8190b191faac8f67065b |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f497bc12b881908fe3386c66252bf6 |
completed | May 1, 2026, 12:08 p.m. |
| PD | Predicate disambiguation | batch_69f49366e8d08190adb4b71fe3a14683 |
completed | May 1, 2026, 11:49 a.m. |
Created at: April 18, 2026, 4:50 a.m.