Triple
T2758079
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | York University station |
E61152
|
entity |
| Predicate | hasPrestoMachines |
P42029
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [York University station, hasPrestoMachines, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPrestoMachines Context triple: [York University station, hasPrestoMachines, yes]
-
A.
hasRapids
Indicates that a body of water contains sections of fast-flowing, turbulent water known as rapids.
-
B.
hasSupercomputer
Indicates that an entity possesses, controls, or is equipped with a supercomputer.
-
C.
hasITCluster
Indicates that an entity possesses, hosts, or is associated with a specific information technology (IT) cluster.
-
D.
hasCP
Indicates that an entity possesses, is associated with, or is characterized by a specific CP (such as a control point, contact person, or configuration parameter), depending on the domain context.
-
E.
hasProvisionOn
Indicates that one entity contains, specifies, or includes a particular provision, clause, or stipulation concerning another entity or subject.
- 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_69ab4b7a85bc819094a349b84beb1f2c |
completed | March 6, 2026, 9:47 p.m. |
| NER | Named-entity recognition | batch_69abdb8ba4688190b401b6eb5b734ac6 |
completed | March 7, 2026, 8:02 a.m. |
| PD | Predicate disambiguation | batch_69abd82de7f48190acd614f28644c6da |
completed | March 7, 2026, 7:47 a.m. |
| PDg | Predicate description generation | batch_69abda0a13308190a986df86270258a7 |
completed | March 7, 2026, 7:55 a.m. |
Created at: March 6, 2026, 9:57 p.m.