Triple
T9230274
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hartz III |
E221798
|
entity |
| Predicate | namedAfter |
P63
|
FINISHED |
| Object | Peter Hartz |
E779191
|
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: Peter Hartz | Statement: [Hartz III, namedAfter, Peter Hartz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Peter Hartz Context triple: [Hartz III, namedAfter, Peter Hartz]
-
A.
Peter Hartz
chosen
Peter Hartz is a German manager and former Volkswagen executive best known for designing the controversial labor market reforms in Germany commonly referred to as the Hartz reforms.
-
B.
Dietmar Schwab
Dietmar Schwab is a relatively obscure individual sharing the common German surname Schwab, with no widely documented public achievements or roles.
-
C.
Norbert Schultze
Norbert Schultze was a German composer best known for his film scores and popular songs, including the World War II-era hit "Lili Marleen."
-
D.
Klaus Tschira
Klaus Tschira was a German physicist, entrepreneur, and philanthropist best known as one of the co-founders of the software company SAP.
-
E.
Heinrich Wörner
Heinrich Wörner is a German architect best known for designing the main building of the Topography of Terror documentation center in Berlin.
- 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.