Triple

T19714080
Position Surface form Disambiguated ID Type / Status
Subject Suzhou Industrial Park E473427 entity
Predicate cityDistrictStatus P137047 FINISHED
Object county-level administrative district of Suzhou 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: county-level administrative district of Suzhou | Statement: [Suzhou Industrial Park, cityDistrictStatus, county-level administrative district of Suzhou]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: cityDistrictStatus
Context triple: [Suzhou Industrial Park, cityDistrictStatus, county-level administrative district of Suzhou]
  • A. cityCenterStatus
    Indicates whether a location holds the status of being the central or main area of a city.
  • B. cityStatusContext
    Indicates the contextual status or role that a city holds within a broader administrative, political, or situational framework.
  • C. cityStatusUntil
    Indicates the period up to a specified time during which a place holds or held a particular city status.
  • D. cityDistrictLevel
    Indicates that one administrative unit is a district-level subdivision within a given city in the territorial hierarchy.
  • E. cityDistrictFunction
    Indicates that a specific function, role, or land-use purpose is assigned to or characterizes a particular district within a city.
  • F. None of above. chosen

Provenance (4 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_69d8e516dd048190a0b6c93ea3e71f58 completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e6440b47508190a8a33325b00841dc completed April 20, 2026, 3:19 p.m.
PD Predicate disambiguation batch_69e530438c60819082364c7be3eef6f0 completed April 19, 2026, 7:42 p.m.
PDg Predicate description generation batch_69e532bbedf081908d801600e2af94a7 completed April 19, 2026, 7:53 p.m.
Created at: April 10, 2026, 1:46 p.m.