Triple

T9299201
Position Surface form Disambiguated ID Type / Status
Subject USS Macon (ZRS-5) E223717 entity
Predicate hullNumber P3152 FINISHED
Object ZRS-5
ZRS-5 was the hull designation of USS Macon, a U.S. Navy rigid airship and flying aircraft carrier operated in the early 1930s.
 E789613 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: ZRS-5 | Statement: [USS Macon (ZRS-5), hullNumber, ZRS-5]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: ZRS-5
Context triple: [USS Macon (ZRS-5), hullNumber, ZRS-5]
  • A. ZS
    ZS is the vehicle registration code assigned to cars registered in the Polish city of Szczecin.
  • B. ZS
    ZS is the stock ticker symbol for Zscaler, a cloud-based information security company traded on the NASDAQ.
  • C. RZ
    RZ is the vehicle registration code used on license plates for the district of Lauenburg in the German state of Schleswig-Holstein.
  • D. ZSU
    ZSU is the commonly used Ukrainian abbreviation for the Armed Forces of Ukraine, the country's unified military organization.
  • E. WZL-5
    WZL-5 is a major Polish aerospace and defense maintenance and repair facility specializing in the overhaul and modernization of military aircraft and helicopters.
  • 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: ZRS-5
Triple: [USS Macon (ZRS-5), hullNumber, ZRS-5]
Generated description
ZRS-5 was the hull designation of USS Macon, a U.S. Navy rigid airship and flying aircraft carrier operated in the early 1930s.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: ZRS-5
Target entity description: ZRS-5 was the hull designation of USS Macon, a U.S. Navy rigid airship and flying aircraft carrier operated in the early 1930s.
  • A. ZS
    ZS is the stock ticker symbol for Zscaler, a cloud-based information security company traded on the NASDAQ.
  • B. ZS
    ZS is the vehicle registration code assigned to cars registered in the Polish city of Szczecin.
  • C. RZ
    RZ is the vehicle registration code used on license plates for the district of Lauenburg in the German state of Schleswig-Holstein.
  • D. ZSU
    ZSU is the commonly used Ukrainian abbreviation for the Armed Forces of Ukraine, the country's unified military organization.
  • E. WZL-5
    WZL-5 is a major Polish aerospace and defense maintenance and repair facility specializing in the overhaul and modernization of military aircraft and helicopters.
  • 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_69ca8423edb08190bc0c91287a484768 completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd08cf50cc8190a025f478dff4f9fd completed April 1, 2026, noon
NED1 Entity disambiguation (via context triple) batch_69d0b25ac97881908751b466b370b7e5 completed April 4, 2026, 6:40 a.m.
NEDg Description generation batch_69d0b301659481909c1865884421fcde completed April 4, 2026, 6:43 a.m.
NED2 Entity disambiguation (via description) batch_69d0b38ae1ec8190b36019d3a642290d completed April 4, 2026, 6:45 a.m.
Created at: March 30, 2026, 7:36 p.m.