Triple
T12433286
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Richard Huelsenbeck |
E297083
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Huelsenbeck |
E297083
|
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: Huelsenbeck | Statement: [Richard Huelsenbeck, familyName, Huelsenbeck]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Huelsenbeck Context triple: [Richard Huelsenbeck, familyName, Huelsenbeck]
-
A.
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.
-
B.
Eldredge
Eldredge is a surname and given name that functions as a spelling variant of Eldridge, borne by various individuals in English-speaking countries.
-
C.
Richard Huelsenbeck
chosen
Richard Huelsenbeck was a German poet, writer, and psychoanalyst who was a leading founding member and theorist of the Dada movement in Zurich and Berlin.
-
D.
Gribskov
Gribskov is one of Denmark’s largest and oldest forests, known for its diverse woodland landscapes, rich wildlife, and extensive network of walking and cycling trails.
-
E.
Hufstedler
Hufstedler is the surname of Shirley Hufstedler, a prominent American judge and the first U.S. Secretary of Education.
- 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_69d6ada0640c81908c061d7fb3d47786 |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d94d804c2c819082f2f86edcbb50de |
completed | April 10, 2026, 7:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6349d29c481909a37fd386cc06575 |
completed | May 2, 2026, 5:30 p.m. |
Created at: April 8, 2026, 9:55 p.m.