Triple
T8815594
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Biedenharn family |
E209767
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Biedenharn |
E758636
|
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: Biedenharn | Statement: [Biedenharn family, familyName, Biedenharn]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Biedenharn Context triple: [Biedenharn family, familyName, Biedenharn]
-
A.
Biedenharn
chosen
Biedenharn is a surname most notably associated with Joseph A. Biedenharn, an early bottler of Coca-Cola and prominent American businessman.
-
B.
Benedenberg
Benedenberg is a small village in the Dutch province of South Holland, located within the municipality of Krimpenerwaard.
-
C.
Löwenthal
Löwenthal is the maiden surname of Elsa Einstein, who was both the second wife and cousin of physicist Albert Einstein.
-
D.
Hohberg
Hohberg is a municipality in the Ortenau district of Baden-Württemberg in southwestern Germany.
-
E.
Braunshardt
Braunshardt is a district of the town of Weiterstadt in the state of Hesse, Germany.
- 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_69ca8363f3308190a47e3f1ebd51f613 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5ff2ff248190bafcafe8b3860e53 |
completed | March 31, 2026, 11:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cf89357b488190997f368079ef7e1e |
completed | April 3, 2026, 9:32 a.m. |
Created at: March 30, 2026, 6:45 p.m.