Triple

T23931495
Position Surface form Disambiguated ID Type / Status
Subject Greenwich, Massachusetts E602509 entity
Predicate hadRailStation P89322 FINISHED
Object Greenwich station
Greenwich station was a former railroad station that served the now-submerged town of Greenwich in Massachusetts before its flooding for the creation of the Quabbin Reservoir.
 E1607812 NE FINISHED

How this triple was built (3 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: Greenwich station | Statement: [Greenwich, Massachusetts, hadRailStation, Greenwich station]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Greenwich station
Triple: [Greenwich, Massachusetts, hadRailStation, Greenwich station]
Generated description
Greenwich station was a former railroad station that served the now-submerged town of Greenwich in Massachusetts before its flooding for the creation of the Quabbin Reservoir.
PD Predicate disambiguation gpt-5-mini-2025-08-07 
Target predicate: hadRailStation
Context triple: [Greenwich, Massachusetts, hadRailStation, Greenwich station]
  • A. hadRailwayStation chosen
    Indicates that a place or area previously possessed a railway station, which may no longer be in existence or operation.
  • B. hasRailStation
    Indicates that one entity possesses, contains, or is served by a rail station.
  • C. hasRailwayStation
    Indicates that a place or location is served by, or contains, a railway station.
  • D. hasHeritageRailwayStation
    Indicates that an entity possesses or is associated with a railway station that is preserved or operated as a heritage or historical railway facility.
  • E. hasRailwayStationRole
    Indicates that an entity holds or is assigned a specific functional role or capacity within the operation or management of a railway station.
  • F. None of above.

Provenance (6 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_69e2953b928c819095395fa87baca583 completed April 17, 2026, 8:16 p.m.
NER Named-entity recognition batch_69f1cf9c223881908e5fa4b5564848e6 completed April 29, 2026, 9:30 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0f76451b908190b22fa8d08f918818 completed May 21, 2026, 9:16 p.m.
NEDg Description generation batch_6a0f77372e188190bbf5c1a77de0833c completed May 21, 2026, 9:20 p.m.
NED2 Entity disambiguation (via description) batch_6a0f77d47ea08190828e5f5f9f0e3899 completed May 21, 2026, 9:23 p.m.
PD Predicate disambiguation batch_69f16151ebdc819086e9e1d7cc1f4f3c completed April 29, 2026, 1:39 a.m.
Created at: April 17, 2026, 8:58 p.m.