Triple

T7465581
Position Surface form Disambiguated ID Type / Status
Subject German Army military schools E176363 entity
Predicate militaryBranch P253 FINISHED
Object Heer E9485 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: Heer | Statement: [German Army military schools, militaryBranch, Heer]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Heer
Context triple: [German Army military schools, militaryBranch, Heer]
  • A. Heer chosen
    The Heer was the land-based component of Nazi Germany’s armed forces, serving as its primary army during World War II.
  • B. Heer
    Heer is the tragic heroine of the classic Punjabi romantic epic "Heer Ranjha," renowned as a symbol of eternal love and devotion.
  • C. Heriz
    Heriz is a renowned carpet-weaving region in northwestern Iran, famous for its durable hand-knotted rugs featuring bold geometric medallion designs.
  • D. Heers
    Heers is a rural municipality in the Belgian province of Limburg, known for its agricultural landscape and historic villages.
  • E. Henreid
    Henreid is the surname of Paul Henreid, the Austrian-born actor and director best known for his roles in classic Hollywood films such as "Casablanca" and "Now, Voyager."
  • 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_69c69f21632481908bf83f6c6da897e3 completed March 27, 2026, 3:15 p.m.
NER Named-entity recognition batch_69c6f3f28f34819080713a8abcc22034 completed March 27, 2026, 9:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8346adb3081908f049d8dcd623215 completed March 28, 2026, 8:04 p.m.
Created at: March 27, 2026, 3:40 p.m.