Triple

T13587950
Position Surface form Disambiguated ID Type / Status
Subject Tawang railway station E324617 entity
Predicate hasTracksCount P1707 FINISHED
Object multiple tracks 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: multiple tracks | Statement: [Tawang railway station, hasTracksCount, multiple tracks]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasTracksCount
Context triple: [Tawang railway station, hasTracksCount, multiple tracks]
  • A. numberOfTracks chosen
    Indicates the quantity of tracks associated with a given entity.
  • B. hasTrack
    Indicates that one entity possesses, includes, or is associated with a specific track (such as a path, course, or recorded item).
  • C. hasTwoTracks
    Indicates that the subject possesses or is associated with exactly two distinct tracks or pathways.
  • D. hasTailTracks
    Indicates that an entity exhibits or leaves behind tail-shaped tracks or imprints as evidence of its movement or presence.
  • E. containsAdditionalTracksBeyond
    Indicates that one entity includes more tracks or items than are present in another referenced set or version.
  • F. None of above.

Provenance (3 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_69d80769100c819099111274614f5ed2 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbb054c6008190839384ce26e8f71a completed April 12, 2026, 2:46 p.m.
PD Predicate disambiguation batch_69dbae18eaf48190809e8b365856cde9 completed April 12, 2026, 2:37 p.m.
Created at: April 9, 2026, 9:49 p.m.