Triple

T31423833
Position Surface form Disambiguated ID Type / Status
Subject Saint-Lazare (Paris Métro) E801604 entity
Predicate adjacentStationOnLine13 P180352 FINISHED
Object Miromesnil (Paris Métro) NE NERFINISHED

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: Miromesnil (Paris Métro) | Statement: [Saint-Lazare (Paris Métro), adjacentStationOnLine13, Miromesnil (Paris Métro)]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: adjacentStationOnLine13
Context triple: [Saint-Lazare (Paris Métro), adjacentStationOnLine13, Miromesnil (Paris Métro)]
  • A. adjacentStationOnLine12
    Indicates that one station is directly next to another station along transit line 12, with no other stations in between on that line.
  • B. adjacentStationOnLine10
    Indicates that two stations are directly next to each other along transit line 10, with no other station between them on that line.
  • C. adjacentStationOnLine
    Indicates that one station is directly next to another station along the same transit line, with no other station in between.
  • D. adjacentStationOnLineD
    Indicates that one station is directly next to another station along line D, with no other stations in between on that line.
  • E. adjacentStationOnLine3
    Indicates that one station is directly next to another station along transit line 3, with no other stations in between on that line.
  • 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_69f348c26f048190b4adadd71b4596c5 completed April 30, 2026, 12:19 p.m.
NER Named-entity recognition batch_69f73ae120bc8190bff94d38d7a7a00d completed May 3, 2026, 12:09 p.m.
PD Predicate disambiguation batch_69f73a38d0848190aa5139144b8561c6 completed May 3, 2026, 12:06 p.m.
PDg Predicate description generation batch_69f73adfd9a081908adae6bd59dfefb9 completed May 3, 2026, 12:09 p.m.
Created at: April 30, 2026, 8:51 p.m.