Triple
T1551729
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Central station (MBTA) |
E33105
|
entity |
| Predicate | hasVentilationShafts |
P31158
|
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: [Central station (MBTA), hasVentilationShafts, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasVentilationShafts Context triple: [Central station (MBTA), hasVentilationShafts, yes]
-
A.
hasVentilationBuildings
Indicates that certain buildings are designated to provide ventilation for another structure, area, or system.
-
B.
airShaftsLead
Indicates that one or more air shafts provide a passage or connection that leads from a source location to a destination location.
-
C.
hasSeparateEntrances
Indicates that the related entities each have their own distinct entrance, rather than sharing a common one.
-
D.
hasNumberOfFireplaces
Indicates the specific count of fireplaces associated with an entity.
-
E.
airIntakeType
Indicates the type or configuration of the system or mechanism used to draw air into an engine or device.
- 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_69a885ee6db8819099502bc5ce8af881 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69aa574094048190a2d7fc3ac904d51e |
completed | March 6, 2026, 4:25 a.m. |
| PD | Predicate disambiguation | batch_69a907b426dc8190975c024a50955368 |
completed | March 5, 2026, 4:33 a.m. |
| PDg | Predicate description generation | batch_69aa573ee8e0819084abf59f1ddbd1da |
completed | March 6, 2026, 4:25 a.m. |
Created at: March 4, 2026, 7:26 p.m.