Triple
T2826436
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fenway station |
E54933
|
entity |
| Predicate | openedAsRailroadStop |
P1712
|
FINISHED |
| Object | 19th century |
—
|
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: 19th century | Statement: [Fenway station, openedAsRailroadStop, 19th century]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: openedAsRailroadStop Context triple: [Fenway station, openedAsRailroadStop, 19th century]
-
A.
openedAsRailStop
chosen
Indicates that an entity began operation or was first established specifically as a railway stop.
-
B.
openedAsRedLineStation
Indicates that a station began operation specifically as part of the Red Line when it first opened.
-
C.
hasRailStation
Indicates that one entity possesses, contains, or is served by a rail station.
-
D.
openedToRailTraffic
Indicates that a rail line, track, or related infrastructure has begun operating and is officially available for use by train traffic.
-
E.
openedAsMBTAStation
Indicates that an entity began operation specifically as an MBTA station at a particular time.
- 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_69ab49e100c0819082a40cb797383243 |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abde94ba848190b2c990936e07e6bb |
completed | March 7, 2026, 8:15 a.m. |
| PD | Predicate disambiguation | batch_69abdd0acab881909e8c25cbef83678c |
completed | March 7, 2026, 8:08 a.m. |
Created at: March 6, 2026, 9:59 p.m.