Triple

T14844325
Position Surface form Disambiguated ID Type / Status
Subject Gillingham E349045 entity
Predicate hasNeighbourhood P4813 FINISHED
Object Ham
Ham is a residential area and suburb within the town of Gillingham in Kent, England.
E1123242 NE FINISHED

How this triple was built (4 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: Ham | Statement: [Gillingham, hasNeighbourhood, Ham]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ham
Context triple: [Gillingham, hasNeighbourhood, Ham]
  • A. Ham
    Ham is a suburban riverside district in southwest London, England, known for its historic houses, green spaces, and proximity to the River Thames.
  • B. Ham
    Ham is a small town in the Somme department of northern France, known historically for its medieval fortress and strategic location.
  • C. Ham
    Ham is a biblical figure known as one of Noah’s sons and a progenitor of several ancient peoples mentioned in the Hebrew Bible.
  • D. Ham
    Ham is a municipality in the Belgian province of Limburg, known for its rural character and location in the Flemish Region.
  • E. HAM
    HAM is the IATA airport code for Hamburg Airport, the international airport serving the city of Hamburg, Germany.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
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: Ham
Triple: [Gillingham, hasNeighbourhood, Ham]
Generated description
Ham is a residential area and suburb within the town of Gillingham in Kent, England.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Ham
Target entity description: Ham is a residential area and suburb within the town of Gillingham in Kent, England.
  • A. Ham
    Ham is a suburban riverside district in southwest London, England, known for its historic houses, green spaces, and proximity to the River Thames.
  • B. Ham
    Ham is a small town in the Somme department of northern France, known historically for its medieval fortress and strategic location.
  • C. Ham
    Ham is a biblical figure known as one of Noah’s sons and a progenitor of several ancient peoples mentioned in the Hebrew Bible.
  • D. Ham
    Ham is a municipality in the Belgian province of Limburg, known for its rural character and location in the Flemish Region.
  • E. HAM
    HAM is the IATA airport code for Hamburg Airport, the international airport serving the city of Hamburg, Germany.
  • F. None of above. chosen

Provenance (5 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_69d822ec69008190a9232caa68836872 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69ded291103c8190a64cfe700bfee197 completed April 14, 2026, 11:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe64fe89e88190912cd205feef85d3 completed May 8, 2026, 10:34 p.m.
NEDg Description generation batch_69fe660250ec819084aed06983e0df06 completed May 8, 2026, 10:38 p.m.
NED2 Entity disambiguation (via description) batch_69fe667bed5c81909832d09228595533 completed May 8, 2026, 10:41 p.m.
Created at: April 10, 2026, 1:53 a.m.