Triple
T5580676
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Günther Sabetzki |
E146631
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Sabetzki |
E146631
|
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: Sabetzki | Statement: [Günther Sabetzki, familyName, Sabetzki]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sabetzki Context triple: [Günther Sabetzki, familyName, Sabetzki]
-
A.
Sabetzki
chosen
Sabetzki is a German surname most notably associated with Günther Sabetzki, a prominent ice hockey executive and former president of the International Ice Hockey Federation.
-
B.
Lalo
Lalo is a common Spanish nickname for the given name Eduardo.
-
C.
Guabiraba
Guabiraba is a neighborhood and administrative district located in the northern part of Recife, in the state of Pernambuco, Brazil.
-
D.
Cáqueza
Cáqueza is a small municipality and town in the Andean region of central Colombia, known for its rural landscapes and proximity to Bogotá in the department of Cundinamarca.
-
E.
Gabrielino
Gabrielino refers to the Indigenous Tongva people native to the Los Angeles Basin and Southern Channel Islands in California.
- 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_69c0090287a08190b4098411effe970c |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c0206d62548190b8a3c6efc1825661 |
completed | March 22, 2026, 5:01 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c0285baa648190bf8e94740ea62466 |
completed | March 22, 2026, 5:35 p.m. |
Created at: March 22, 2026, 3:37 p.m.