Triple
T11170730
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lutzenberg |
E264265
|
entity |
| Predicate | hasSettlement |
P1068
|
FINISHED |
| Object |
Hof
Hof is a small settlement within the municipality of Lutzenberg in the Swiss canton of Appenzell Ausserrhoden.
|
E908872
|
NE FINISHED |
How this triple was built (4 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: Hof | Statement: [Lutzenberg, hasSettlement, Hof]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hof Context triple: [Lutzenberg, hasSettlement, Hof]
-
A.
Hof
Hof is a town in northeastern Bavaria, Germany, known for its location near the Czech border and its regional cultural and economic significance.
-
B.
Heiderhof
Heiderhof is a residential subdistrict of the Bonn borough Bad Godesberg in western Germany.
-
C.
Hever
Hever is a village in Kent, England, best known as the location of the historic Hever Castle, former childhood home of Anne Boleyn.
-
D.
Hohberg
Hohberg is a municipality in the Ortenau district of Baden-Württemberg in southwestern Germany.
-
E.
Idstein
Idstein is a historic town in the German state of Hesse, known for its well-preserved medieval old town and timber-framed architecture.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Hof Triple: [Lutzenberg, hasSettlement, Hof]
Generated description
Hof is a small settlement within the municipality of Lutzenberg in the Swiss canton of Appenzell Ausserrhoden.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Hof Target entity description: Hof is a small settlement within the municipality of Lutzenberg in the Swiss canton of Appenzell Ausserrhoden.
-
A.
Hof
Hof is a town in northeastern Bavaria, Germany, known for its location near the Czech border and its regional cultural and economic significance.
-
B.
Heiderhof
Heiderhof is a residential subdistrict of the Bonn borough Bad Godesberg in western Germany.
-
C.
Hever
Hever is a village in Kent, England, best known as the location of the historic Hever Castle, former childhood home of Anne Boleyn.
-
D.
Hohberg
Hohberg is a municipality in the Ortenau district of Baden-Württemberg in southwestern Germany.
-
E.
Idstein
Idstein is a historic town in the German state of Hesse, known for its well-preserved medieval old town and timber-framed architecture.
- F. None of above. chosen
Provenance (5 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_69d6aa9dafac8190bd90d2c74f661aa7 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e8952e248190b0751669e8c960b7 |
completed | April 9, 2026, 5:57 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e463b155a08190b361b38a39d25b1f |
completed | April 19, 2026, 5:10 a.m. |
| NEDg | Description generation | batch_69e46c37efec81908aa709587c37569d |
completed | April 19, 2026, 5:46 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69e47292cdd08190b05c4c8b09f4f918 |
completed | April 19, 2026, 6:13 a.m. |
Created at: April 8, 2026, 9:29 p.m.