Triple
T406813
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ayer station |
E9400
|
entity |
| Predicate | hasZoneSystem |
P6793
|
FINISHED |
| Object | MBTA Commuter Rail zone-based fares |
—
|
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 Commuter Rail zone-based fares | Statement: [Ayer station, hasZoneSystem, MBTA Commuter Rail zone-based fares]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasZoneSystem Context triple: [Ayer station, hasZoneSystem, MBTA Commuter Rail zone-based fares]
-
A.
hasZone
chosen
Indicates that one entity possesses, contains, or is associated with a specific zone or designated area.
-
B.
hasTimeZones
Indicates that an entity is associated with one or more time zones in which it is valid or operates.
-
C.
hasDaylightSavingVariant
Indicates that one time-related entity is the daylight saving time version or counterpart of another standard-time entity.
-
D.
isCanonicalZone
Indicates that a given zone is the primary, standard, or officially recognized version among possible alternatives.
-
E.
timeZoneType
Indicates the classification or category of a time zone associated with an entity (e.g., standard, daylight, or specific time zone format/type).
- 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_69a2e80111fc8190961d5b7c6154123f |
completed | Feb. 28, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69a2ecbd766c8190bb8a91605929156a |
completed | Feb. 28, 2026, 1:25 p.m. |
| PD | Predicate disambiguation | batch_69a2e971a3a481909e6b075f25dd234a |
completed | Feb. 28, 2026, 1:11 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.