Triple
T179322
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kakutani fixed-point theorem |
E3648
|
entity |
| Predicate | impliesExistenceOf |
P1661
|
FINISHED |
| Object | fixed point of a correspondence |
—
|
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: fixed point of a correspondence | Statement: [Kakutani fixed-point theorem, impliesExistenceOf, fixed point of a correspondence]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: impliesExistenceOf Context triple: [Kakutani fixed-point theorem, impliesExistenceOf, fixed point of a correspondence]
-
A.
implies
chosen
Indicates that the truth of one statement guarantees or leads logically to the truth of another statement.
-
B.
providedFor
Indicates that one entity supplies, furnishes, or makes something available to or on behalf of another entity for its use or benefit.
-
C.
doesNotImply
Indicates that the truth of one statement or condition does not guarantee or lead to the truth of another statement or condition.
-
D.
assumes
Indicates that one entity takes on, accepts, or presumes a role, responsibility, state, or fact regarding another entity or situation.
-
E.
providesEvidenceFor
Indicates that one entity serves as support, justification, or proof for the validity or truth of another entity.
- 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_69a25374990081909766d30c79a18e0e |
completed | Feb. 28, 2026, 2:31 a.m. |
| NER | Named-entity recognition | batch_69a25900709c8190a65e778936be5dd5 |
completed | Feb. 28, 2026, 2:54 a.m. |
| PD | Predicate disambiguation | batch_69a2566b53d481909c0ed40dd3719e8c |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:39 a.m.