Triple
T5555929
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Donald Klopfer |
E145639
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Klopfer |
E86636
|
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: Klopfer | Statement: [Donald Klopfer, familyName, Klopfer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Klopfer Context triple: [Donald Klopfer, familyName, Klopfer]
-
A.
Klopfer
chosen
Klopfer is a German surname most notably associated with Gerhard Klopfer, a Nazi official involved in high-level administrative functions during the Third Reich.
-
B.
Klopas
Klopas is a Greek-American former professional soccer player and coach best known for his time with the Chicago Fire and the U.S. national team.
-
C.
Hölldobler
Hölldobler is a German surname most notably associated with Bert Hölldobler, a prominent behavioral ecologist and myrmecologist known for his research on ants.
-
D.
Körner
Körner is a German surname borne by various notable figures in fields such as literature, music, and politics.
-
E.
Klecko
Klecko is the surname of former American football defensive lineman Joe Klecko, best known for his standout career with the New York Jets as part of the “New York Sack Exchange.”
- 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_69c008fcaf788190bafa02a1917ee73b |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c01ffc5e7c81908e1c454d3bfd357b |
completed | March 22, 2026, 4:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c0283bd408819085c62caf254df339 |
completed | March 22, 2026, 5:34 p.m. |
Created at: March 22, 2026, 3:36 p.m.