Triple

T2634296
Position Surface form Disambiguated ID Type / Status
Subject Circle line E59707 entity
Predicate rollingStock P1305 FINISHED
Object S7 Stock
S7 Stock is a type of London Underground train used on the Circle and other sub-surface lines, featuring air-conditioning, walk-through carriages, and modern passenger information systems.
E283347 NE FINISHED

How this triple was built (4 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: S7 Stock | Statement: [Circle line, rollingStock, S7 Stock]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: S7 Stock
Context triple: [Circle line, rollingStock, S7 Stock]
  • A. S7
    S7 is a Berlin S-Bahn rapid transit line that runs across the city, connecting key districts between Potsdam and Ahrensfelde.
  • B. S7
    S7 is the IATA airline designator for S7 Airlines, a major Russian carrier based in Novosibirsk.
  • C. S75
    S75 is a line of the Berlin S-Bahn urban rail network serving routes within the Berlin metropolitan area.
  • D. S7 Priority
    S7 Priority is the frequent flyer loyalty program of Russian carrier S7 Airlines, offering members tiered status levels, mileage accrual, and various travel benefits.
  • E. UP-78
    UP-78 is the vehicle registration code assigned to motor vehicles registered in Kanpur, Uttar Pradesh, India.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
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: S7 Stock
Triple: [Circle line, rollingStock, S7 Stock]
Generated description
S7 Stock is a type of London Underground train used on the Circle and other sub-surface lines, featuring air-conditioning, walk-through carriages, and modern passenger information systems.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: S7 Stock
Target entity description: S7 Stock is a type of London Underground train used on the Circle and other sub-surface lines, featuring air-conditioning, walk-through carriages, and modern passenger information systems.
  • A. S7
    S7 is a Berlin S-Bahn rapid transit line that runs across the city, connecting key districts between Potsdam and Ahrensfelde.
  • B. S7
    S7 is the IATA airline designator for S7 Airlines, a major Russian carrier based in Novosibirsk.
  • C. S75
    S75 is a line of the Berlin S-Bahn urban rail network serving routes within the Berlin metropolitan area.
  • D. S7 Priority
    S7 Priority is the frequent flyer loyalty program of Russian carrier S7 Airlines, offering members tiered status levels, mileage accrual, and various travel benefits.
  • E. UP-78
    UP-78 is the vehicle registration code assigned to motor vehicles registered in Kanpur, Uttar Pradesh, India.
  • F. None of above. chosen

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_69ab4ac8596c8190b34997e73d9e991c completed March 6, 2026, 9:44 p.m.
NER Named-entity recognition batch_69abd8def9bc8190b2e013abffc7b191 completed March 7, 2026, 7:50 a.m.
NED1 Entity disambiguation (via context triple) batch_69af90ac94d48190b3138abac9934ec8 completed March 10, 2026, 3:31 a.m.
NEDg Description generation batch_69af91625bd481908d3666af3cd3733f completed March 10, 2026, 3:34 a.m.
NED2 Entity disambiguation (via description) batch_69af91f9e1208190aa149c9afc84911c completed March 10, 2026, 3:37 a.m.
Created at: March 6, 2026, 9:50 p.m.