Triple
T26255132
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Farey sequence |
E656694
|
entity |
| Predicate | endpointInclusion |
P160988
|
FINISHED |
| Object | includes both 0 and 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: includes both 0 and 1 | Statement: [Farey sequence, endpointInclusion, includes both 0 and 1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: endpointInclusion Context triple: [Farey sequence, endpointInclusion, includes both 0 and 1]
-
A.
endPoint
Indicates the terminal location, limit, or final state reached by an object, process, or path in a given relationship or action.
-
B.
endpointFeature
Indicates that a particular feature, capability, or characteristic is associated with, provided by, or available at a specific endpoint.
-
C.
typicalEndpoint
Indicates that something represents the standard or commonly used endpoint associated with another entity or process.
-
D.
endPointExample
Indicates that something serves as a representative or illustrative instance of a particular endpoint.
-
E.
secondaryEndpoint
Indicates that something serves as an additional, non-primary endpoint or target associated with a main endpoint in a relationship or process.
- 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_69ee5b4d25ac819086acb51184602576 |
completed | April 26, 2026, 6:37 p.m. |
| NER | Named-entity recognition | batch_69f60dfaeebc8190ac01d3a0030acf55 |
completed | May 2, 2026, 2:45 p.m. |
| PD | Predicate disambiguation | batch_69f60b874cc88190a487230abb69efea |
completed | May 2, 2026, 2:34 p.m. |
| PDg | Predicate description generation | batch_69f60c68b02c8190870758d79cdec68b |
completed | May 2, 2026, 2:38 p.m. |
Created at: April 26, 2026, 9:08 p.m.