Triple

T32477105
Position Surface form Disambiguated ID Type / Status
Subject Noida Sector 18 E830004 entity
Predicate hasNearbySector P141258 FINISHED
Object Noida Sector 17
Noida Sector 17 is a residential and commercial neighborhood in Noida, Uttar Pradesh, forming part of the planned sectors of the city near its central market areas.
 E2012707 NE FINISHED

How this triple was built (3 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: Noida Sector 17 | Statement: [Noida Sector 18, hasNearbySector, Noida Sector 17]
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: Noida Sector 17
Triple: [Noida Sector 18, hasNearbySector, Noida Sector 17]
Generated description
Noida Sector 17 is a residential and commercial neighborhood in Noida, Uttar Pradesh, forming part of the planned sectors of the city near its central market areas.
PD Predicate disambiguation gpt-5-mini-2025-08-07 
Target predicate: hasNearbySector
Context triple: [Noida Sector 18, hasNearbySector, Noida Sector 17]
  • A. hasNearbyGeographicalArea chosen
    Indicates that one geographical area is located in close spatial proximity to another geographical area.
  • B. hasNearbySquare
    Indicates that one entity has at least one square-shaped entity located close to it in space.
  • C. hasNearbyPrecinct
    Indicates that one location has a police precinct or similar administrative station situated close to it in geographic proximity.
  • D. hasNearbyEntityType
    Indicates that an entity has at least one other entity of a specified type located within a defined nearby spatial or contextual range.
  • E. hasNearbyBoundary
    Indicates that one entity’s boundary lies close to, but does not necessarily touch or coincide with, the boundary of another entity.
  • F. None of above.

Provenance (6 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_69f3491ff3b48190b50a7fa00bb05b1f completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69ff49f888348190b9c55afa73b99e6a completed May 9, 2026, 2:51 p.m.
NED1 Entity disambiguation (via context triple) batch_6a347b7499f881909f8ac097078d81f3 completed June 18, 2026, 11:12 p.m.
NEDg Description generation batch_6a347cb4b3848190badc3f8bf4d184e8 completed June 18, 2026, 11:18 p.m.
NED2 Entity disambiguation (via description) batch_6a347da3535081908263b33d3a3045fa completed June 18, 2026, 11:22 p.m.
PD Predicate disambiguation batch_69ff49614ef88190ac70b034c55ad738 completed May 9, 2026, 2:49 p.m.
Created at: May 1, 2026, 12:58 a.m.