Triple
T19573378
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hannes Löhr |
E489780
|
entity |
| Predicate | placeOfBirth |
P1
|
FINISHED |
| Object | Eitorf |
—
|
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: Eitorf | Statement: [Hannes Löhr, placeOfBirth, Eitorf]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Eitorf Context triple: [Hannes Löhr, placeOfBirth, Eitorf]
-
A.
Eitorf
chosen
Eitorf is a municipality in western Germany situated along the River Sieg in the state of North Rhine-Westphalia.
-
B.
Andorf
Andorf is a market town in the Innviertel region of Upper Austria, known for its rural character and local agricultural economy.
-
C.
Wunstorf
Wunstorf is a town in Lower Saxony, Germany, known for its nearby military air base and its location near the Steinhuder Meer.
-
D.
Espelkamp
Espelkamp is a small town in North Rhine-Westphalia, Germany, known for its post-war planned layout and light industrial economy.
-
E.
Dierdorf
Dierdorf is a surname most prominently associated with former American football player and sportscaster Dan Dierdorf.
- 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_69d8e8dd9374819098e36349b3211663 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e6402228488190b5649d4bbd34d019 |
completed | April 20, 2026, 3:02 p.m. |
Created at: April 10, 2026, 1:42 p.m.