Triple
T16768482
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Johan Harmen Rudolf Köhler |
E407529
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Harmen
Harmen is the given name of Johan Harmen Rudolf Köhler, a Dutch-born military officer who became a general in the Royal Netherlands East Indies Army in the 19th century.
|
E1232204
|
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: Harmen | Statement: [Johan Harmen Rudolf Köhler, givenName, Harmen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Harmen Context triple: [Johan Harmen Rudolf Köhler, givenName, Harmen]
-
A.
Hendrik
Hendrik is a masculine given name of Germanic origin, commonly used in Dutch- and German-speaking countries and related to the name Henry.
-
B.
Leendert
Leendert is a Dutch masculine given name, notably borne by mathematician Bartel Leendert van der Waerden.
-
C.
Dirck
Dirck is a Dutch masculine given name historically borne by several notable figures, including artists of the Dutch Golden Age.
-
D.
Joris
Joris is a Dutch designer best known for his innovative, technology-driven furniture and experimental design projects.
-
E.
Willem
Willem is a given name, primarily used in Dutch-speaking regions, that corresponds to the English name William.
- 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: Harmen Triple: [Johan Harmen Rudolf Köhler, givenName, Harmen]
Generated description
Harmen is the given name of Johan Harmen Rudolf Köhler, a Dutch-born military officer who became a general in the Royal Netherlands East Indies Army in the 19th century.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Harmen Target entity description: Harmen is the given name of Johan Harmen Rudolf Köhler, a Dutch-born military officer who became a general in the Royal Netherlands East Indies Army in the 19th century.
-
A.
Hendrik
Hendrik is a masculine given name of Germanic origin, commonly used in Dutch- and German-speaking countries and related to the name Henry.
-
B.
Leendert
Leendert is a Dutch masculine given name, notably borne by mathematician Bartel Leendert van der Waerden.
-
C.
Dirck
Dirck is a Dutch masculine given name historically borne by several notable figures, including artists of the Dutch Golden Age.
-
D.
Joris
Joris is a Dutch designer best known for his innovative, technology-driven furniture and experimental design projects.
-
E.
Willem
Willem is a given name, primarily used in Dutch-speaking regions, that corresponds to the English name William.
- 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_69d8839174188190909f190097207065 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3b0349bc88190938750f1e5af192a |
completed | April 18, 2026, 4:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00a533e83481909966a7b86c8c8e64 |
completed | May 10, 2026, 3:33 p.m. |
| NEDg | Description generation | batch_6a00a6d6a6d08190b103c2dfd30f0e28 |
completed | May 10, 2026, 3:40 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a00a749f2688190af57bd13b9dedeb1 |
completed | May 10, 2026, 3:42 p.m. |
Created at: April 10, 2026, 5:21 a.m.