Triple

T25026777
Position Surface form Disambiguated ID Type / Status
Subject ZSAM E626730 entity
Predicate associatedRunwayLocation P105006 FINISHED
Object Gaoqi area of Xiamen
The Gaoqi area of Xiamen is an urban district on Xiamen Island in Fujian, China, known for hosting Xiamen Gaoqi International Airport and significant industrial and commercial facilities.
 E1663027 NE FINISHED

How this triple was built (3 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: Gaoqi area of Xiamen | Statement: [ZSAM, associatedRunwayLocation, Gaoqi area of Xiamen]
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: Gaoqi area of Xiamen
Triple: [ZSAM, associatedRunwayLocation, Gaoqi area of Xiamen]
Generated description
The Gaoqi area of Xiamen is an urban district on Xiamen Island in Fujian, China, known for hosting Xiamen Gaoqi International Airport and significant industrial and commercial facilities.
PD Predicate disambiguation gpt-5-mini-2025-08-07 
Target predicate: associatedRunwayLocation
Context triple: [ZSAM, associatedRunwayLocation, Gaoqi area of Xiamen]
  • A. associatedWithRunways chosen
    Indicates a relationship where something (such as an object, facility, or feature) is linked or connected to one or more runways.
  • B. runwayAdjacentTo
    Indicates that a runway is directly next to or alongside another feature or area, with no significant separation between them.
  • C. isPrimaryRunwayOf
    Indicates that a runway serves as the main or principal runway for a particular airport or airfield.
  • D. runwayName
    Indicates the designated name or identifier assigned to a runway.
  • E. runwayInformationAvailableIn
    Indicates that information about a runway is available within or through a specified medium, source, or context.
  • F. None of above.

Provenance (6 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_69e2ff28ee3881909c626af002457a4a completed April 18, 2026, 3:48 a.m.
NER Named-entity recognition batch_69f70e8755a48190931eaa77946f9460 completed May 3, 2026, 8:59 a.m.
NED1 Entity disambiguation (via context triple) batch_6a1048b998988190917417b2f8130d60 completed May 22, 2026, 12:14 p.m.
NEDg Description generation batch_6a104a6d40f88190941fae4e53c175f7 completed May 22, 2026, 12:22 p.m.
NED2 Entity disambiguation (via description) batch_6a104c2d8308819097b21b979944585e completed May 22, 2026, 12:29 p.m.
PD Predicate disambiguation batch_69f70abc00848190a1c3f495ef6c8dc6 completed May 3, 2026, 8:43 a.m.
Created at: April 18, 2026, 6:07 a.m.