Triple

T33796308
Position Surface form Disambiguated ID Type / Status
Subject Taikoo Shing E866082 entity
Predicate associatedWithIndustryHistory P3008 FINISHED
Object shipbuilding in Hong Kong 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: shipbuilding in Hong Kong | Statement: [Taikoo Shing, associatedWithIndustryHistory, shipbuilding in Hong Kong]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: associatedWithIndustryHistory
Context triple: [Taikoo Shing, associatedWithIndustryHistory, shipbuilding in Hong Kong]
  • A. hasHistoricIndustry chosen
    Indicates that an entity has been associated with a notable or historically significant industry or industrial activity in the past.
  • B. historicallyLinked
    Indicates that two entities are connected through a shared or related historical event, period, or development.
  • C. hasIndustrialHeritage
    Indicates that an entity possesses or is associated with historically significant industrial sites, structures, or practices.
  • D. associatedWithCityHistory
    Indicates a relationship where something is connected or relevant to the historical events, development, or heritage of a particular city.
  • E. associatedWithMilitaryHistory
    Indicates a relationship in which something is connected or relevant to military history, such as events, figures, institutions, or artifacts.
  • 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_69f3498f99f481909cb271f4965a7594 completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_6a037e0953908190b2930b3c06a40129 completed May 12, 2026, 7:22 p.m.
PD Predicate disambiguation batch_6a0379f6c3308190b954f7810214ceed completed May 12, 2026, 7:05 p.m.
Created at: May 1, 2026, 1:46 a.m.