Triple
T11367925
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ryan Suter |
E269259
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Suter |
E170401
|
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: Suter | Statement: [Ryan Suter, familyName, Suter]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Suter Context triple: [Ryan Suter, familyName, Suter]
-
A.
Suter
chosen
Suter is a surname of Germanic origin, often associated with individuals of Swiss or German heritage.
-
B.
Kleiser
Kleiser is a surname most notably associated with American film director Randal Kleiser, known for directing the musical romantic comedy "Grease."
-
C.
Mennekes
Mennekes is a German electrical engineering company best known in e-mobility for developing the widely adopted Type 2 AC charging connector for electric vehicles.
-
D.
Huntziger
Huntziger is a French surname most notably borne by General Charles Huntziger, a senior French Army officer during the World Wars.
-
E.
Biqueli
Biqueli is a small coastal settlement on Atauro Island in East Timor, known for its fishing community and proximity to coral reefs.
- 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_69d6aacca1048190b39dbbc2174616fa |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7ea89e1148190b0ca29db9d7e2cbd |
completed | April 9, 2026, 6:06 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e556718fc481908543ed4bc5fe3d6e |
completed | April 19, 2026, 10:25 p.m. |
Created at: April 8, 2026, 9:33 p.m.