Triple
T30556903
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Franklin, Massachusetts |
E777722
|
entity |
| Predicate | hasMBTACommuterRailTerminus |
P169846
|
FINISHED |
| Object | Franklin Line |
—
|
NE NERFINISHED |
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: Franklin Line | Statement: [Franklin, Massachusetts, hasMBTACommuterRailTerminus, Franklin Line]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMBTACommuterRailTerminus Context triple: [Franklin, Massachusetts, hasMBTACommuterRailTerminus, Franklin Line]
-
A.
amtrakStation
Indicates that one entity is an Amtrak train station serving the other entity or located at the specified place.
-
B.
hasMetroTerminus
Indicates that one location serves as the terminal (end) station of a metro line for another location.
-
C.
isSuburbanRailway
Indicates that a railway line, service, or system operates primarily within and around a metropolitan area, typically connecting the city center with its suburbs.
-
D.
hasRailStation
Indicates that one entity possesses, contains, or is served by a rail station.
-
E.
nearCommuterRailStation
Indicates that one entity is located close to, or within a short walking distance of, a commuter rail station.
- 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_69f2249ed41c8190b175170ecfd6e1c5 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f688d564a88190b78eebeb163b76f6 |
completed | May 2, 2026, 11:29 p.m. |
| PD | Predicate disambiguation | batch_69f67e42d6688190b60e91d2c388c555 |
completed | May 2, 2026, 10:44 p.m. |
| PDg | Predicate description generation | batch_69f6827a7b9c8190ab13605aacc81df9 |
completed | May 2, 2026, 11:02 p.m. |
Created at: April 29, 2026, 8:20 p.m.