Triple

T10143169
Position Surface form Disambiguated ID Type / Status
Subject III Corps E231636 entity
Predicate nickname P55 FINISHED
Object Phantom Corps E631574 NE FINISHED

How this triple was built (2 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: Phantom Corps | Statement: [III Corps, nickname, Phantom Corps]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Phantom Corps
Context triple: [III Corps, nickname, Phantom Corps]
  • A. Phantom Corps chosen
    Phantom Corps is the nickname of the U.S. Army’s III Armored Corps, a major tactical formation known for commanding heavy armored and mechanized forces.
  • B. Phantoms
    Phantoms is a horror novel by Dean Koontz that follows two sisters and a small-town sheriff confronting a mysterious, ancient evil that has wiped out an entire Colorado town.
  • C. Phantom
    Phantom is a hostile flying undead mob in Minecraft that swoops down from the night sky to attack players who haven’t slept for several days.
  • D. Phantom
    Phantom is a music production alias associated with Ye (formerly Kanye West), under which he has created and produced tracks.
  • E. Phantom’s Revenge
    Phantom’s Revenge is a high-speed steel roller coaster at Kennywood amusement park near Pittsburgh, Pennsylvania, known for its intense airtime and dramatic terrain-hugging drops.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69ca848364f881908a24366a6feec1db completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cdeb273fec8190818707167e031d58 completed April 2, 2026, 4:05 a.m.
NED1 Entity disambiguation (via context triple) batch_69d2e618b0bc8190bc1d6f15dac2708e completed April 5, 2026, 10:45 p.m.
Created at: March 30, 2026, 9:07 p.m.