Triple
T23158789
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kreis Freiberg |
E578521
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Hainichen |
—
|
NE NERFINISHED |
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: Hainichen | Statement: [Kreis Freiberg, contains, Hainichen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hainichen Context triple: [Kreis Freiberg, contains, Hainichen]
-
A.
Hainichen
chosen
Hainichen is a small town in the Free State of Saxony in eastern Germany, known for its historical architecture and location between the cities of Chemnitz and Dresden.
-
B.
Eichelbaum
Eichelbaum is a German-language surname borne by various individuals, including figures in law, arts, and public life.
-
C.
Ichenhausen
Ichenhausen is a small town in the Bavarian region of Swabia in southern Germany, known for its historic architecture and former Jewish community.
-
D.
Hohne
Hohne is a village in Lower Saxony, Germany, historically notable for its military garrison and association with British Army units.
-
E.
Hohnstein
Hohnstein is a small historic town in Saxony, Germany, known for its medieval castle and scenic location in the Saxon Switzerland region.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e245fc75348190a0288401044c8af8 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f18efeddd48190b6d03d2146583dcc |
completed | April 29, 2026, 4:54 a.m. |
Created at: April 17, 2026, 4:02 p.m.