Triple
T11624660
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pete Hornberger |
E276231
|
entity |
| Predicate | colleague |
P398
|
FINISHED |
| Object | Lutz |
E107498
|
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: Lutz | Statement: [Pete Hornberger, colleague, Lutz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lutz Context triple: [Pete Hornberger, colleague, Lutz]
-
A.
Lutz
chosen
Lutz is a masculine given name of German origin commonly used in German-speaking countries.
-
B.
Lutze
Lutze is a German surname most notably associated with Viktor Lutze, a high-ranking Nazi official and head of the Sturmabteilung (SA) in the 1930s.
-
C.
Getzlaf
Getzlaf is a surname most prominently associated with Canadian former NHL star Ryan Getzlaf, a long-time captain of the Anaheim Ducks.
-
D.
Nepela
Nepela is a Slovak surname most notably associated with Ondrej Nepela, an Olympic and world champion figure skater.
-
E.
Lennertz
Lennertz is a German-origin surname borne by various individuals, including American composer Christopher Lennertz.
- 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_69d6aafa51148190ab84940694c00235 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a12416908190ac2dcd7f7ebb308f |
completed | April 10, 2026, 7:05 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ee87745b388190a78958fa0c08b89b |
completed | April 26, 2026, 9:45 p.m. |
Created at: April 8, 2026, 9:39 p.m.