Triple

T5337657
Position Surface form Disambiguated ID Type / Status
Subject Bel Air E123864 entity
Predicate typicalLotSize P50716 FINISHED
Object large lots 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: large lots | Statement: [Bel Air, typicalLotSize, large lots]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: typicalLotSize
Context triple: [Bel Air, typicalLotSize, large lots]
  • A. hasLotSize
    Indicates that an entity possesses a specific amount or extent of physical area, typically referring to the size of a parcel of land or property lot.
  • B. hasLotSizeType chosen
    Indicates the classification or category used to describe the size of a lot or parcel.
  • C. typicalUnitSize
    Indicates the standard or most common size or quantity in which something is typically measured, packaged, or used.
  • D. typicalInvestmentSize
    Indicates the usual or most common amount of money invested in a single investment or deal.
  • E. typicalCapacity
    Indicates the usual or standard amount, volume, or capability that something is designed or expected to hold, handle, or perform under normal conditions.
  • 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_69bd464b07f8819095aa76577c9829e4 completed March 20, 2026, 1:06 p.m.
NER Named-entity recognition batch_69bd85c6ec008190ad7a8a54360387d8 completed March 20, 2026, 5:37 p.m.
PD Predicate disambiguation batch_69bd84583dbc819088a03e3afb30178c completed March 20, 2026, 5:31 p.m.
Created at: March 20, 2026, 2 p.m.