Triple
T16893918
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Erongo Mountains |
E424247
|
entity |
| Predicate | highestPointName |
P210
|
FINISHED |
| Object |
Hohenfels
Hohenfels is a prominent peak in Namibia’s Erongo Mountains, known as the range’s highest summit.
|
E1239953
|
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: Hohenfels | Statement: [Erongo Mountains, highestPointName, Hohenfels]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hohenfels Context triple: [Erongo Mountains, highestPointName, Hohenfels]
-
A.
Grafenwöhr
Grafenwöhr is a Bavarian town best known for hosting one of the largest U.S. Army training areas in Europe.
-
B.
Hohenfels, Germany
Hohenfels, Germany is a Bavarian town best known for hosting a major U.S. Army and NATO training area, including the Joint Multinational Readiness Center.
-
C.
Sembach Kaserne
Sembach Kaserne is a former U.S. military installation near Kaiserslautern, Germany, that served as a key base for American air and ground forces during the Cold War and beyond.
-
D.
Daenner Kaserne
Daenner Kaserne is a U.S. Army installation in Kaiserslautern, Germany, that supports American military operations and community activities in the region.
-
E.
Vockenhausen
Vockenhausen is a district of the town of Eppstein in the German state of Hesse.
- 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: Hohenfels Triple: [Erongo Mountains, highestPointName, Hohenfels]
Generated description
Hohenfels is a prominent peak in Namibia’s Erongo Mountains, known as the range’s highest summit.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Hohenfels Target entity description: Hohenfels is a prominent peak in Namibia’s Erongo Mountains, known as the range’s highest summit.
-
A.
Grafenwöhr
Grafenwöhr is a Bavarian town best known for hosting one of the largest U.S. Army training areas in Europe.
-
B.
Hohenfels, Germany
Hohenfels, Germany is a Bavarian town best known for hosting a major U.S. Army and NATO training area, including the Joint Multinational Readiness Center.
-
C.
Sembach Kaserne
Sembach Kaserne is a former U.S. military installation near Kaiserslautern, Germany, that served as a key base for American air and ground forces during the Cold War and beyond.
-
D.
Daenner Kaserne
Daenner Kaserne is a U.S. Army installation in Kaiserslautern, Germany, that supports American military operations and community activities in the region.
-
E.
Vockenhausen
Vockenhausen is a district of the town of Eppstein in the German state of Hesse.
- 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_69d889da3e8c8190a2b118f383f0beac |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e3c8d6bfc88190b6b47b89c1135871 |
completed | April 18, 2026, 6:09 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00c7aa83bc8190832d2f3903ce0081 |
completed | May 10, 2026, 6 p.m. |
| NEDg | Description generation | batch_6a00c8b9e4888190b25dd3256fc13dd1 |
completed | May 10, 2026, 6:04 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a00c9672ab881909770b4fe551ec622 |
completed | May 10, 2026, 6:07 p.m. |
Created at: April 10, 2026, 5:29 a.m.