Triple

T9230287
Position Surface form Disambiguated ID Type / Status
Subject Hartz III E221798 entity
Predicate relatedTo P37 FINISHED
Object Hartz I E218918 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: Hartz I | Statement: [Hartz III, relatedTo, Hartz I]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hartz I
Context triple: [Hartz III, relatedTo, Hartz I]
  • A. Hartz I chosen
    Hartz I was the first package of German labor market reforms in the early 2000s, aimed at modernizing employment services and promoting job placement and temporary work.
  • B. Hartz III
    Hartz III was a German labor market reform package implemented in the early 2000s that restructured the Federal Employment Agency to improve job placement and labor market services.
  • C. Hartz II
    Hartz II is a German labor market reform package introduced in the early 2000s that, among other measures, created new forms of marginal employment such as “Mini-jobs” and “Midi-jobs” to increase labor market flexibility.
  • D. Hart
    Hart is a local government district and civil parish area in Hampshire, England, known for its high quality of life and largely rural character.
  • E. Hart
    Hart is a surname most famously associated with Moss Hart, the acclaimed American playwright and theater director known for works like "You Can't Take It with You" and "Once in a Lifetime."
  • 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_69ca83ed628c8190bc02d641e57f097f completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69ccee17a2dc8190b373f78be7247f0d completed April 1, 2026, 10:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69d077a789f0819087d7f7612bbeaf6a completed April 4, 2026, 2:29 a.m.
Created at: March 30, 2026, 7:29 p.m.