Triple
T1551721
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Central station (MBTA) |
E33105
|
entity |
| Predicate | hasSignageStandard |
P1739
|
FINISHED |
| Object | MBTA subway signage |
—
|
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: MBTA subway signage | Statement: [Central station (MBTA), hasSignageStandard, MBTA subway signage]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSignageStandard Context triple: [Central station (MBTA), hasSignageStandard, MBTA subway signage]
-
A.
signageStandard
chosen
Indicates that something conforms to, follows, or specifies a particular standard or convention for signage.
-
B.
hasSignage
Indicates that appropriate signs or visual markers are present to convey information, directions, warnings, or identification related to the associated entity.
-
C.
hasSignageName
Indicates that an entity has a specific name or label as it appears on its physical signage.
-
D.
hasHazardSignage
Indicates that appropriate warning or hazard signs are present to alert people to potential dangers associated with the entity.
-
E.
officialLanguageOfSignage
Indicates that a particular language is the one officially used on public signs and signage within a given place or context.
- F. None of above.
Provenance (3 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. |
Created at: March 4, 2026, 7:26 p.m.