Triple

T33153441
Position Surface form Disambiguated ID Type / Status
Subject Tobu Urban Park Line E848500 entity
Predicate hasRollingStock P1305 FINISHED
Object Tobu 8000 series EMU
The Tobu 8000 series EMU is a long-serving Japanese electric multiple unit train type operated by Tobu Railway, widely used on its suburban commuter lines since the 1960s.
 E2040223 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: Tobu 8000 series EMU | Statement: [Tobu Urban Park Line, hasRollingStock, Tobu 8000 series EMU]
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: Tobu 8000 series EMU
Triple: [Tobu Urban Park Line, hasRollingStock, Tobu 8000 series EMU]
Generated description
The Tobu 8000 series EMU is a long-serving Japanese electric multiple unit train type operated by Tobu Railway, widely used on its suburban commuter lines since the 1960s.

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_69f3495a458c8190a1d34b237ba0be3f completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69f6d8dd0f708190a9f04f7b997b777c completed May 3, 2026, 5:10 a.m.
NED1 Entity disambiguation (via context triple) batch_6a3525bc4868819083b20bc3839649be completed June 19, 2026, 11:19 a.m.
NEDg Description generation batch_6a35297c2b508190bd2205d8e6b49afb completed June 19, 2026, 11:35 a.m.
NED2 Entity disambiguation (via description) batch_6a3529cf5238819099801755f5345c3e completed June 19, 2026, 11:36 a.m.
Created at: May 1, 2026, 1:28 a.m.