Triple

T30470952
Position Surface form Disambiguated ID Type / Status
Subject SEPTA NHSL E775289 entity
Predicate depot P14646 FINISHED
Object 69th Street yard
69th Street yard is a SEPTA maintenance and storage facility serving the Norristown High Speed Line near the 69th Street Transportation Center in Upper Darby, Pennsylvania.
 E1916963 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: 69th Street yard | Statement: [SEPTA NHSL, depot, 69th Street yard]
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: 69th Street yard
Triple: [SEPTA NHSL, depot, 69th Street yard]
Generated description
69th Street yard is a SEPTA maintenance and storage facility serving the Norristown High Speed Line near the 69th Street Transportation Center in Upper Darby, Pennsylvania.

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_69f2249622a48190b1fae2e3e4ee958a completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f68715ad9c8190a5f41313c3f11190 completed May 2, 2026, 11:21 p.m.
NED1 Entity disambiguation (via context triple) batch_6a27ac1eedac8190bcd6a078cd2f0684 completed June 9, 2026, 6:01 a.m.
NEDg Description generation batch_6a27acd96c448190b597825a60709338 completed June 9, 2026, 6:04 a.m.
NED2 Entity disambiguation (via description) batch_6a27ad7fb6408190a3a03a28aaa3dcc0 completed June 9, 2026, 6:06 a.m.
Created at: April 29, 2026, 8:11 p.m.