Triple

T895150
Position Surface form Disambiguated ID Type / Status
Subject Honus Wagner E19327 entity
Predicate nickname P55 FINISHED
Object Hans E75878 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: Hans | Statement: [Honus Wagner, nickname, Hans]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hans
Context triple: [Honus Wagner, nickname, Hans]
  • A. Hans chosen
    Hans is a masculine given name of Germanic origin commonly used in Germanic and Scandinavian countries.
  • B. Helmut
    Helmut is a masculine given name of German origin, historically common in German-speaking countries.
  • C. Oskar
    Oskar is a masculine given name of Germanic origin, commonly used in various European countries.
  • D. Karl
    Karl Schwarzschild was a German physicist and astronomer best known for providing the first exact solution to Einstein’s field equations, leading to the concept of the Schwarzschild black hole.
  • E. Karl
    Karl is the given first name of Charles Proteus Steinmetz, the renowned German-American mathematician and electrical engineer who revolutionized the understanding of alternating current systems.
  • 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_69a4939d37188190848be3d426ebc9ae completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4ad22b6fc819093e655c8ce1f738b completed March 1, 2026, 9:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69ace540122c8190824f6de78dc1a411 completed March 8, 2026, 2:56 a.m.
Created at: March 1, 2026, 7:39 p.m.