Triple

T4224206
Position Surface form Disambiguated ID Type / Status
Subject River Lee E94414 entity
Predicate passesThrough P225 FINISHED
Object Hackney E143459 NE 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: Hackney | Statement: [River Lee, passesThrough, Hackney]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hackney
Context triple: [River Lee, passesThrough, Hackney]
  • A. Hammersmith
    Hammersmith is a district in West London known as a major commercial and transport hub along the River Thames.
  • B. Southwark
    Southwark is a historic district in central London on the south bank of the River Thames, known for landmarks such as Borough Market, The Shard, and Shakespeare’s Globe.
  • C. Islington
    Islington is a vibrant inner London borough in England known for its dense urban character, cultural venues, and strong football heritage.
  • D. London Borough of Hackney chosen
    The London Borough of Hackney is an inner London borough in East London known for its diverse communities, vibrant arts and nightlife scenes, and rapid urban regeneration.
  • E. Shoreditch
    Shoreditch is a vibrant East London district known for its creative industries, street art, nightlife, and tech startups.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69b3453700a08190ae88792e3dc63207 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b34e4bf6088190926b982039a12079 completed March 12, 2026, 11:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69be777b514081909832a8a520a7f7d1 completed March 21, 2026, 10:48 a.m.
Created at: March 12, 2026, 11:04 p.m.