Triple
T5610590
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aqueduct–North Conduit Avenue |
E147344
|
entity |
| Predicate | hasWindScreens |
P64652
|
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: [Aqueduct–North Conduit Avenue, hasWindScreens, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWindScreens Context triple: [Aqueduct–North Conduit Avenue, hasWindScreens, yes]
-
A.
hasRetractableRoofPanels
Indicates that an object is equipped with roof panels that can be extended or withdrawn, allowing the roof to open or close as needed.
-
B.
hasFlankVents
Indicates that an entity possesses vents located on its sides or flanks.
-
C.
hasAirConditioning
Indicates that an entity is equipped with or provides air conditioning.
-
D.
hasPlatformScreenDoors
Indicates that a transit station or platform is equipped with platform screen doors separating passengers from the tracks.
-
E.
hasHatchback
Indicates that one entity possesses or is characterized by having a hatchback-style vehicle or body type.
- 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_69c0090500f881908374285baf0ac46f |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c0211dfc88819097b6d4254a61f65a |
completed | March 22, 2026, 5:04 p.m. |
| PD | Predicate disambiguation | batch_69c01b1b3c98819080687d18ab10a914 |
completed | March 22, 2026, 4:38 p.m. |
| PDg | Predicate description generation | batch_69c01f0684908190ae2d14f0bd2ab892 |
completed | March 22, 2026, 4:55 p.m. |
Created at: March 22, 2026, 3:39 p.m.