Triple

T5602114
Position Surface form Disambiguated ID Type / Status
Subject Zeke E147143 entity
Predicate referredAircraftCommonName P64993 FINISHED
Object Zero E144703 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: Zero | Statement: [Zeke, referredAircraftCommonName, Zero]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Zero
Context triple: [Zeke, referredAircraftCommonName, Zero]
  • A. Zero chosen
    Zero is the common nickname for the Mitsubishi A6M Zero, a highly maneuverable Japanese carrier-based fighter aircraft used extensively during World War II.
  • B. Numero Zero
    Numero Zero is a satirical novel by Umberto Eco that explores media manipulation, conspiracy theories, and the construction of history through a failed newspaper’s editorial team in 1990s Italy.
  • C. Code to Zero
    Code to Zero is a Cold War-era thriller novel by Ken Follett that follows an amnesiac rocket scientist uncovering a conspiracy tied to the early days of the space race.
  • D. Never
    Never was the historical name of the Russian town now known as Skovorodino in Amur Oblast.
  • E. Zero K
    Zero K is a 2016 novel by Don DeLillo that explores themes of mortality, technology, and cryonics through a meditative, dystopian narrative.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: referredAircraftCommonName
Context triple: [Zeke, referredAircraftCommonName, Zero]
  • A. usedOnAircraftName
    Indicates that something is employed or applied on an aircraft identified by a specific name.
  • B. notableAircraftCallsign
    Indicates that a particular aircraft is notably associated with, or commonly identified by, a specific callsign.
  • C. commonAircraftFamily
    Indicates that two aircraft belong to the same aircraft family or series, sharing a common design lineage.
  • D. carrierAircraft
    Indicates that an aircraft is designed, equipped, or used to operate from an aircraft carrier.
  • E. aircraftType
    Indicates the specific model or category of aircraft associated with an entity or event.
  • 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_69c009043d648190a7af89698ccf1e3e completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c020dbd6dc8190ba011876c205754e completed March 22, 2026, 5:03 p.m.
NED1 Entity disambiguation (via context triple) batch_69c04d40049881908bf32e4932094c52 completed March 22, 2026, 8:12 p.m.
PD Predicate disambiguation batch_69c01b1890ec8190b9e6fa488792e4d4 completed March 22, 2026, 4:38 p.m.
PDg Predicate description generation batch_69c01f4032408190a4f0d2eb21ebd870 completed March 22, 2026, 4:56 p.m.
Created at: March 22, 2026, 3:39 p.m.