Triple

T2358503
Position Surface form Disambiguated ID Type / Status
Subject Flying Pencil E47212 entity
Predicate notableVariant P4680 FINISHED
Object Do 17Z
The Do 17Z was the most widely produced and refined bomber version of Germany’s Dornier Do 17 “Flying Pencil,” used extensively by the Luftwaffe in the early years of World War II.
 E258008 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: Do 17Z | Statement: [Flying Pencil, notableVariant, Do 17Z]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Do 17Z
Context triple: [Flying Pencil, notableVariant, Do 17Z]
  • A. ZS
    ZS is the vehicle registration code assigned to cars registered in the Polish city of Szczecin.
  • B. Z/28
    The Z/28 is a high-performance, track-focused variant of the Chevrolet Camaro known for its enhanced handling, braking, and power.
  • C. ZM
    ZM is the stock ticker symbol for Zoom Video Communications, a leading provider of cloud-based video conferencing and online collaboration services.
  • D. WZ
    WZ is the IATA airline designator assigned to Red Wings Airlines, a Russian passenger carrier.
  • E. ZUE
    ZUE is the railway station code for Zürich Hauptbahnhof, Switzerland’s largest and busiest train station and a major European rail hub.
  • 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: Do 17Z
Triple: [Flying Pencil, notableVariant, Do 17Z]
Generated description
The Do 17Z was the most widely produced and refined bomber version of Germany’s Dornier Do 17 “Flying Pencil,” used extensively by the Luftwaffe in the early years of World War II.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Do 17Z
Target entity description: The Do 17Z was the most widely produced and refined bomber version of Germany’s Dornier Do 17 “Flying Pencil,” used extensively by the Luftwaffe in the early years of World War II.
  • A. ZS
    ZS is the vehicle registration code assigned to cars registered in the Polish city of Szczecin.
  • B. Z/28
    The Z/28 is a high-performance, track-focused variant of the Chevrolet Camaro known for its enhanced handling, braking, and power.
  • C. ZM
    ZM is the stock ticker symbol for Zoom Video Communications, a leading provider of cloud-based video conferencing and online collaboration services.
  • D. WZ
    WZ is the IATA airline designator assigned to Red Wings Airlines, a Russian passenger carrier.
  • E. ZUE
    ZUE is the railway station code for Zürich Hauptbahnhof, Switzerland’s largest and busiest train station and a major European rail hub.
  • 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_69a88a1a4a6081908645b0f2914521ab completed March 4, 2026, 7:38 p.m.
NER Named-entity recognition batch_69abc71f767481908dfa9be209ea3c5a completed March 7, 2026, 6:35 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae9638ef948190adf945aba42fac76 completed March 9, 2026, 9:43 a.m.
NEDg Description generation batch_69ae96fc0b508190b1da6aa41cddc488 completed March 9, 2026, 9:46 a.m.
NED2 Entity disambiguation (via description) batch_69ae977e539c81909cef638cc61e5ec1 completed March 9, 2026, 9:48 a.m.
Created at: March 4, 2026, 7:55 p.m.