Triple

T15497357
Position Surface form Disambiguated ID Type / Status
Subject S1 Line (Beijing Subway) E378852 entity
Predicate isFirstOfTypeInCity P118479 FINISHED
Object first maglev line in Beijing Subway LITERAL 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: first maglev line in Beijing Subway | Statement: [S1 Line (Beijing Subway), isFirstOfTypeInCity, first maglev line in Beijing Subway]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: isFirstOfTypeInCity
Context triple: [S1 Line (Beijing Subway), isFirstOfTypeInCity, first maglev line in Beijing Subway]
  • A. isInCity
    Indicates that one entity is located within the geographical boundaries of a specified city.
  • B. isOnlyCityIn
    Indicates that one city is the sole city within a specified region, area, or administrative division, with no other cities present there.
  • C. isCityOf
    Indicates that one entity is a city that belongs to, is located within, or is administratively part of another entity (such as a country, state, or region).
  • D. hasRelativePositionInCity
    Indicates that one entity occupies a specific spatial or positional relationship within the boundaries or layout of a particular city.
  • E. isInSameCityAs
    Indicates that two entities are located within the boundaries of the same city.
  • F. None of above. chosen

Provenance (4 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_69d85cd53a7c819080f5b9042c4c199e completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e03fb0aee081909db1c54349ec8492 completed April 16, 2026, 1:47 a.m.
PD Predicate disambiguation batch_69ded2874b788190999158e0f043be21 completed April 14, 2026, 11:49 p.m.
PDg Predicate description generation batch_69ded5deee00819099fa3e43313312e1 completed April 15, 2026, 12:03 a.m.
Created at: April 10, 2026, 3:53 a.m.