Triple

T4203388
Position Surface form Disambiguated ID Type / Status
Subject JAXA Tsukuba Space Center E86123 entity
Predicate abbreviation P43 FINISHED
Object TKSC
TKSC is the primary JAXA facility in Tsukuba, Japan, responsible for mission control, astronaut training, and development and testing of space technologies.
 E420825 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: TKSC | Statement: [JAXA Tsukuba Space Center, abbreviation, TKSC]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: TKSC
Context triple: [JAXA Tsukuba Space Center, abbreviation, TKSC]
  • A. TSK
    TSK is the abbreviation for the Turkish Armed Forces, the military organization responsible for the defense and security of Turkey.
  • B. TSK
    TSK is the vehicle registration code assigned to the city of Skarżysko-Kamienna in Poland.
  • C. SKC
    SKC is the commonly used abbreviation for Sporting Kansas City, a professional Major League Soccer club based in Kansas City.
  • D. TK
    TK is the two-letter IATA airline designator used to identify Turkish Airlines in global aviation systems.
  • E. KTTS
    KTTS is the ICAO airport code for the Shuttle Landing Facility at NASA’s Kennedy Space Center in Florida, a specialized runway used primarily for space shuttle and space-related aircraft operations.
  • 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: TKSC
Triple: [JAXA Tsukuba Space Center, abbreviation, TKSC]
Generated description
TKSC is the primary JAXA facility in Tsukuba, Japan, responsible for mission control, astronaut training, and development and testing of space technologies.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: TKSC
Target entity description: TKSC is the primary JAXA facility in Tsukuba, Japan, responsible for mission control, astronaut training, and development and testing of space technologies.
  • A. TSK
    TSK is the abbreviation for the Turkish Armed Forces, the military organization responsible for the defense and security of Turkey.
  • B. TSK
    TSK is the vehicle registration code assigned to the city of Skarżysko-Kamienna in Poland.
  • C. SKC
    SKC is the commonly used abbreviation for Sporting Kansas City, a professional Major League Soccer club based in Kansas City.
  • D. TK
    TK is the two-letter IATA airline designator used to identify Turkish Airlines in global aviation systems.
  • E. KTTS
    KTTS is the ICAO airport code for the Shuttle Landing Facility at NASA’s Kennedy Space Center in Florida, a specialized runway used primarily for space shuttle and space-related aircraft operations.
  • 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_69aed93b89f48190a31f6d57c760e42f completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69af0380d470819091ffdb1161437266 completed March 9, 2026, 5:29 p.m.
NED1 Entity disambiguation (via context triple) batch_69b58a173a78819094915f63c8411602 completed March 14, 2026, 4:17 p.m.
NEDg Description generation batch_69b58e1e7bc08190b75486c74953f609 completed March 14, 2026, 4:34 p.m.
NED2 Entity disambiguation (via description) batch_69b58e7a208481909056b6fba4597bf4 completed March 14, 2026, 4:36 p.m.
Created at: March 9, 2026, 3:49 p.m.