Triple

T36165886
Position Surface form Disambiguated ID Type / Status
Subject Amtrak Cities Sprinter E1045994 entity
Predicate primaryRoute P6298 FINISHED
Object New Haven–Springfield
New Haven–Springfield is a key passenger rail corridor in the northeastern United States connecting New Haven, Connecticut, with Springfield, Massachusetts.
E2172326 NE 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: New Haven–Springfield | Statement: [Amtrak Cities Sprinter, primaryRoute, New Haven–Springfield]
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: New Haven–Springfield
Triple: [Amtrak Cities Sprinter, primaryRoute, New Haven–Springfield]
Generated description
New Haven–Springfield is a key passenger rail corridor in the northeastern United States connecting New Haven, Connecticut, with Springfield, Massachusetts.

Provenance (5 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_69f76e396bc88190b99d221bff9be27a completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7b4f0a82881908f4b674508d9151d completed May 3, 2026, 8:49 p.m.
NED1 Entity disambiguation (via context triple) batch_6a390d56e1108190b794f52d3663617e completed June 22, 2026, 10:24 a.m.
NEDg Description generation batch_6a390eaab52881909027bbc2cc2469ba completed June 22, 2026, 10:30 a.m.
NED2 Entity disambiguation (via description) batch_6a390f6f1ec88190b2fe251699996657 completed June 22, 2026, 10:33 a.m.
Created at: May 3, 2026, 4:08 p.m.