Triple
T28586089
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MBTA Commuter Rail passes |
E723507
|
entity |
| Predicate | includesZoneAccess |
P199040
|
FINISHED |
| Object | all zones between origin and destination |
—
|
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: all zones between origin and destination | Statement: [MBTA Commuter Rail passes, includesZoneAccess, all zones between origin and destination]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: includesZoneAccess Context triple: [MBTA Commuter Rail passes, includesZoneAccess, all zones between origin and destination]
-
A.
hasZone
Indicates that one entity possesses, contains, or is associated with a specific zone or designated area.
-
B.
supportsZoneSystem
Indicates that one entity provides compatibility with or implementation of a specific zone-based system used by another entity.
-
C.
hasZoneStatus
Indicates that a specified zone currently possesses a particular status or condition.
-
D.
usesZoning
Indicates that one entity applies or relies on a zoning scheme, classification, or regulations established or provided by another entity.
-
E.
hasProtectedAreaAccess
Indicates that an entity is permitted to enter, use, or otherwise access a designated protected area under defined conditions.
- 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_69f01d7f92e481909847f5f3f3174a89 |
completed | April 28, 2026, 2:37 a.m. |
| NER | Named-entity recognition | batch_69ff1c91bbac8190b84012dee1cb3b2c |
completed | May 9, 2026, 11:37 a.m. |
| PD | Predicate disambiguation | batch_69ff1c23ca508190bb5a435d765b7e53 |
completed | May 9, 2026, 11:36 a.m. |
| PDg | Predicate description generation | batch_69ff1c90c0f48190a3ede7b36ec77cfd |
completed | May 9, 2026, 11:37 a.m. |
Created at: April 28, 2026, 4:17 a.m.