Triple
T10242135
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Constantin Wilhelm Lambert Gloger |
E243618
|
entity |
| Predicate | hasFamilyName |
P18
|
FINISHED |
| Object |
Gloger
Gloger is a German surname most notably associated with the 19th-century zoologist and ornithologist Constantin Wilhelm Lambert Gloger.
|
E852979
|
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: Gloger | Statement: [Constantin Wilhelm Lambert Gloger, hasFamilyName, Gloger]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gloger Context triple: [Constantin Wilhelm Lambert Gloger, hasFamilyName, Gloger]
-
A.
Sonnemann
Sonnemann is the maiden surname of Emmy Göring, the German actress who became the second wife of Nazi leader Hermann Göring.
-
B.
Vogelmann
Vogelmann is a German-language surname, likely originating as an occupational or descriptive name related to birds.
-
C.
Bischoffen
Bischoffen is a small municipality in the central German state of Hesse, situated in a rural area characterized by forests, hills, and nearby reservoirs.
-
D.
Dietl
Dietl is a German surname most notably associated with Eduard Dietl, a World War II German general.
-
E.
Mollerussa
Mollerussa is a small town in the province of Lleida, Catalonia, Spain, known for its agricultural surroundings and regional commercial services.
- 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: Gloger Triple: [Constantin Wilhelm Lambert Gloger, hasFamilyName, Gloger]
Generated description
Gloger is a German surname most notably associated with the 19th-century zoologist and ornithologist Constantin Wilhelm Lambert Gloger.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Gloger Target entity description: Gloger is a German surname most notably associated with the 19th-century zoologist and ornithologist Constantin Wilhelm Lambert Gloger.
-
A.
Sonnemann
Sonnemann is the maiden surname of Emmy Göring, the German actress who became the second wife of Nazi leader Hermann Göring.
-
B.
Vogelmann
Vogelmann is a German-language surname, likely originating as an occupational or descriptive name related to birds.
-
C.
Bischoffen
Bischoffen is a small municipality in the central German state of Hesse, situated in a rural area characterized by forests, hills, and nearby reservoirs.
-
D.
Dietl
Dietl is a German surname most notably associated with Eduard Dietl, a World War II German general.
-
E.
Mollerussa
Mollerussa is a small town in the province of Lleida, Catalonia, Spain, known for its agricultural surroundings and regional commercial services.
- 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_69d381b0f97c819085c9b45799a5fb7c |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d229c1ac8190a86e911aea47a56d |
completed | April 7, 2026, 9:45 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d6f78a6efc819091f8303a6cfe4c8b |
completed | April 9, 2026, 12:49 a.m. |
| NEDg | Description generation | batch_69d6fcaa16788190a4c7ef79a78febc6 |
completed | April 9, 2026, 1:11 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d6fd6d705c81908e469068937a79b3 |
completed | April 9, 2026, 1:14 a.m. |
Created at: April 6, 2026, 11:25 a.m.