Triple

T10693030
Position Surface form Disambiguated ID Type / Status
Subject Chengdu J-20 E252058 entity
Predicate engineModel P2092 FINISHED
Object WS-10
The WS-10 is a Chinese afterburning turbofan jet engine developed to power modern People's Liberation Army Air Force fighter aircraft.
 E878471 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: WS-10 | Statement: [Chengdu J-20, engineModel, WS-10]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: WS-10
Context triple: [Chengdu J-20, engineModel, WS-10]
  • A. W100
    W100 is the internal Mercedes-Benz chassis code for the ultra-luxury 600 limousine series produced in the 1960s and 1970s.
  • B. TX-10
    TX-10 is the commonly used abbreviation for Texas's 10th congressional district, a U.S. House of Representatives district covering parts of central Texas.
  • C. W7 series
    The W7 series is a high-speed Japanese Shinkansen train type operated by JR West, designed for comfort, safety, and reliable performance on long-distance routes.
  • D. O-10
    O-10 is the highest pay grade for four-star flag and general officers in the U.S. Armed Forces, including admirals and full generals.
  • E. WZL-1
    WZL-1 is a major Polish aerospace and defense company specializing in the maintenance, repair, and modernization of military aircraft and related systems.
  • 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: WS-10
Triple: [Chengdu J-20, engineModel, WS-10]
Generated description
The WS-10 is a Chinese afterburning turbofan jet engine developed to power modern People's Liberation Army Air Force fighter aircraft.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: WS-10
Target entity description: The WS-10 is a Chinese afterburning turbofan jet engine developed to power modern People's Liberation Army Air Force fighter aircraft.
  • A. W100
    W100 is the internal Mercedes-Benz chassis code for the ultra-luxury 600 limousine series produced in the 1960s and 1970s.
  • B. TX-10
    TX-10 is the commonly used abbreviation for Texas's 10th congressional district, a U.S. House of Representatives district covering parts of central Texas.
  • C. W7 series
    The W7 series is a high-speed Japanese Shinkansen train type operated by JR West, designed for comfort, safety, and reliable performance on long-distance routes.
  • D. O-10
    O-10 is the highest pay grade for four-star flag and general officers in the U.S. Armed Forces, including admirals and full generals.
  • E. WZL-1
    WZL-1 is a major Polish aerospace and defense company specializing in the maintenance, repair, and modernization of military aircraft and related systems.
  • 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_69d6aa5bd7c08190a816e733b4045c23 completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d6fd38c24c8190a105a9dfdf705b38 completed April 9, 2026, 1:13 a.m.
NED1 Entity disambiguation (via context triple) batch_69d988ad741c8190b9ae962e0c5bc272 completed April 10, 2026, 11:33 p.m.
NEDg Description generation batch_69d98aecef388190a270e92c93ccca05 completed April 10, 2026, 11:42 p.m.
NED2 Entity disambiguation (via description) batch_69d98c04e8c08190b4d7bc63357c69f4 completed April 10, 2026, 11:47 p.m.
Created at: April 8, 2026, 9:11 p.m.