Triple

T7236260
Position Surface form Disambiguated ID Type / Status
Subject 29th Motorized Infantry Division E155234 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: [29th Motorized Infantry Division, militaryBranch, Heer]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Heer
Context triple: [29th Motorized Infantry Division, militaryBranch, Heer]
  • A. Heer
    Heer is the tragic heroine of the classic Punjabi romantic epic "Heer Ranjha," renowned as a symbol of eternal love and devotion.
  • B. Heer chosen
    The Heer was the land-based component of Nazi Germany’s armed forces, serving as its primary army during World War II.
  • 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_69c688143bfc81908d4176617735e601 completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6ea33dd3481908ebb050e1fab5aaa completed March 27, 2026, 8:36 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7cc32d6c48190ae78b3d1227bb868 completed March 28, 2026, 12:40 p.m.
Created at: March 27, 2026, 2:55 p.m.