Triple
T32395164
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brixton Underground Station |
E827784
|
entity |
| Predicate | isStepFreeToTrain |
P174028
|
FINISHED |
| Object | no |
—
|
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: no | Statement: [Brixton Underground Station, isStepFreeToTrain, no]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isStepFreeToTrain Context triple: [Brixton Underground Station, isStepFreeToTrain, no]
-
A.
canFormTrainOf
Indicates that one entity is capable of being physically or logically connected with another to form a continuous train or sequence.
-
B.
hasBeginnerFriendlyTraining
Indicates that an entity provides training or instructional resources suitable for beginners or those with little prior experience.
-
C.
hasTrainingComplex
Indicates that an entity possesses or is associated with a dedicated facility or complex used for training activities.
-
D.
hasTrainingFor
Indicates that an entity has received or possesses training that prepares it for performing a specific task, role, or function.
-
E.
hasTrainingEnvironment
Indicates that an entity is associated with, or operates within, a specific environment or setting used for training or practice.
- 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_69f349184e7481909c6c54428cb9cf12 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6c2149dbc81908e5069cd30a3f3da |
completed | May 3, 2026, 3:33 a.m. |
| PD | Predicate disambiguation | batch_69f6ba6eb32c8190bf405b2011fa48f7 |
completed | May 3, 2026, 3:01 a.m. |
| PDg | Predicate description generation | batch_69f6bb344bb48190a8089f29c0063ded |
completed | May 3, 2026, 3:04 a.m. |
Created at: May 1, 2026, 12:52 a.m.