Triple
T6993513
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gütermann family |
E162142
|
entity |
| Predicate | hasFamilyName |
P18
|
FINISHED |
| Object | Gütermann |
E162141
|
NE FINISHED |
How this triple was built (2 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: Gütermann | Statement: [Gütermann family, hasFamilyName, Gütermann]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gütermann Context triple: [Gütermann family, hasFamilyName, Gütermann]
-
A.
Gütermann
chosen
Gütermann is a German surname most notably associated with the Gütermann family involved in industry and manufacturing, particularly in the production of sewing threads.
-
B.
Ruländer
Ruländer is a traditional German name for the Pinot Gris grape variety, commonly used for rich, full-bodied white wines.
-
C.
Hammann
Hammann is a German-origin surname borne by various notable individuals in fields such as aviation, music, and academia.
-
D.
Edelmann
Edelmann is a surname of German origin borne by various individuals across fields such as music, sports, and academia.
-
E.
Oberhauser
Oberhauser is a German-language surname borne by various notable individuals across fields such as sports, the arts, and public life.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69c68856d7808190ab33ee914640281b |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6dbc30fdc81909244d83c8178755c |
completed | March 27, 2026, 7:34 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c76a161f088190bbc3c4e2815fa929 |
completed | March 28, 2026, 5:41 a.m. |
Created at: March 27, 2026, 2:32 p.m.