Triple
T1551720
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Central station (MBTA) |
E33105
|
entity |
| Predicate | hasEmergencyExits |
P31156
|
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), hasEmergencyExits, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEmergencyExits Context triple: [Central station (MBTA), hasEmergencyExits, yes]
-
A.
hasNumberOfEntrances
Indicates the relationship that specifies how many entrances an entity possesses.
-
B.
hasEmergencySystems
Indicates that the subject is equipped with or includes systems designed to detect, respond to, or manage emergency situations.
-
C.
hasEmergencyIntercoms
Indicates that an entity is equipped with emergency intercom devices available for use in urgent or crisis situations.
-
D.
hasSeparateEntrances
Indicates that the related entities each have their own distinct entrance, rather than sharing a common one.
-
E.
hasEndDoors
Indicates that an object or structure is equipped with doors located at one or more of its ends.
- 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.