Triple
T15380394
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Max Klinger |
E367782
|
entity |
| Predicate | placeOfDeath |
P21
|
FINISHED |
| Object | Großjena |
E762099
|
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: Großjena | Statement: [Max Klinger, placeOfDeath, Großjena]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Großjena Context triple: [Max Klinger, placeOfDeath, Großjena]
-
A.
Großjena
chosen
Großjena is a village and district of the town of Naumburg in the German state of Saxony-Anhalt, known for its location in the Saale-Unstrut wine-growing region.
-
B.
Weiterstadt
Weiterstadt is a town in the German state of Hesse, located near Darmstadt and known for its residential areas and commercial centers.
-
C.
Gelnhausen
Gelnhausen is a historic town in the German state of Hesse, known for its well-preserved medieval architecture and former status as a Free Imperial City of the Holy Roman Empire.
-
D.
Großeibstadt
Großeibstadt is a small municipality in the Rhön-Grabfeld district of northern Bavaria, Germany, known for its rural character and Franconian village setting.
-
E.
Frohnhausen
Frohnhausen is a district (Ortsteil) of the town of Dillenburg in the Lahn-Dill-Kreis of Hesse, Germany.
- 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_69d85a1551a08190ba2caea7cd51c639 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e61928c81908852c355d537ed9c |
completed | April 16, 2026, 1:41 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff219863b48190a68e73c85e27472c |
completed | May 9, 2026, 11:59 a.m. |
Created at: April 10, 2026, 3:19 a.m.