Triple
T1056925
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brouwer fixed-point theorem |
E22815
|
entity |
| Predicate | nonConstructive |
P22980
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Brouwer fixed-point theorem, nonConstructive, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nonConstructive Context triple: [Brouwer fixed-point theorem, nonConstructive, true]
-
A.
negativeFormulation
Indicates that the associated statement, condition, or requirement is expressed in a negated or prohibitive form rather than an affirmative one.
-
B.
nonPartisan
Indicates that an entity is not affiliated with, influenced by, or acting on behalf of any political party or partisan interest.
-
C.
nonExclusive
Indicates that the relationship or access is shared among multiple parties and is not limited to a single, exclusive holder.
-
D.
doesNot
Indicates that a specified entity lacks, refrains from, or fails to perform a particular action or exhibit a particular property in relation to another entity or context.
-
E.
notRecommendedBy
Indicates that one entity explicitly advises against or does not endorse another entity.
- 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_69a493dada0481909c43649f9843ea91 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b8da80dc8190b79beaf509910725 |
completed | March 1, 2026, 10:08 p.m. |
| PD | Predicate disambiguation | batch_69a4b731e25c8190b5ea8466648c2c9a |
completed | March 1, 2026, 10:01 p.m. |
| PDg | Predicate description generation | batch_69a4b7da38888190a118ef20ce4ae9aa |
completed | March 1, 2026, 10:04 p.m. |
Created at: March 1, 2026, 7:42 p.m.