Triple
T9571526
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | HO |
E230929
|
entity |
| Predicate | usedIn |
P98
|
FINISHED |
| Object | district of Hof |
E246193
|
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: district of Hof | Statement: [HO, usedIn, district of Hof]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: district of Hof Context triple: [HO, usedIn, district of Hof]
-
A.
Hof district
chosen
Hof district is a rural administrative district in the Bavarian region of Upper Franconia in Germany, known for its small towns, agricultural areas, and proximity to the Czech border.
-
B.
Hof (Saale)
Hof (Saale) is a town in northeastern Bavaria, Germany, known as a regional center near the borders with Saxony and the Czech Republic.
-
C.
Bergheim district
Bergheim district is an urban area of Heidelberg, Germany, known for its mix of residential neighborhoods, commercial spaces, and university facilities including the Bergheim campus.
-
D.
Hof
Hof is a town in northeastern Bavaria, Germany, known for its location near the Czech border and its regional cultural and economic significance.
-
E.
Dukenburg district
Dukenburg district is a residential area in the southwestern part of Nijmegen, Netherlands, characterized by post-war housing estates, green spaces, and local shopping facilities.
- 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_69ca847f22188190a56e4a97625bef22 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd998bf20881909fad48ecb16dfa31 |
completed | April 1, 2026, 10:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d152ba8f8081908b11c3c098e7e5f0 |
completed | April 4, 2026, 6:04 p.m. |
Created at: March 30, 2026, 8:04 p.m.