Triple
T14917753
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Swiss nobility |
E371424
|
entity |
| Predicate | includesTitle |
P3254
|
FINISHED |
| Object |
Junker
Junker is a historical noble title, particularly associated with the lower-ranking landed aristocracy in German-speaking regions, including parts of Switzerland.
|
E1126801
|
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: Junker | Statement: [Swiss nobility, includesTitle, Junker]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Junker Context triple: [Swiss nobility, includesTitle, Junker]
-
A.
Junker Jörg
Junker Jörg was the alias used by Martin Luther while he lived in hiding at Wartburg Castle, during which he translated the New Testament into German.
-
B.
Heinrici
Heinrici is a German surname most notably associated with Gotthard Heinrici, a senior Wehrmacht general during World War II.
-
C.
Günther
Günther is the zoologist who first formally described the impressed tortoise species Manouria impressa.
-
D.
Günther
Günther is a German masculine given name traditionally associated with figures of Germanic origin and culture.
-
E.
Leiningen
Leiningen is a popular build automation and project management tool for the Clojure programming language, used to manage dependencies, run tasks, and streamline development workflows.
- 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: Junker Triple: [Swiss nobility, includesTitle, Junker]
Generated description
Junker is a historical noble title, particularly associated with the lower-ranking landed aristocracy in German-speaking regions, including parts of Switzerland.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Junker Target entity description: Junker is a historical noble title, particularly associated with the lower-ranking landed aristocracy in German-speaking regions, including parts of Switzerland.
-
A.
Junker Jörg
Junker Jörg was the alias used by Martin Luther while he lived in hiding at Wartburg Castle, during which he translated the New Testament into German.
-
B.
Heinrici
Heinrici is a German surname most notably associated with Gotthard Heinrici, a senior Wehrmacht general during World War II.
-
C.
Günther
Günther is a German masculine given name traditionally associated with figures of Germanic origin and culture.
-
D.
Günther
Günther is the zoologist who first formally described the impressed tortoise species Manouria impressa.
-
E.
Leiningen
Leiningen is a popular build automation and project management tool for the Clojure programming language, used to manage dependencies, run tasks, and streamline development workflows.
- 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_69d85cc7ea3481908228b5acb7d06f12 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded62038508190946499cd3552990e |
completed | April 15, 2026, 12:04 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe72bf2120819099df39bdc1da691b |
completed | May 8, 2026, 11:33 p.m. |
| NEDg | Description generation | batch_69fe7360c11481908e2e5127b466e31b |
completed | May 8, 2026, 11:36 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fe743c37308190a045ef5f0ade8508 |
completed | May 8, 2026, 11:39 p.m. |
Created at: April 10, 2026, 2:32 a.m.