Triple
T15353155
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brandon Trost |
E367103
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Trost |
E408413
|
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: Trost | Statement: [Brandon Trost, familyName, Trost]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Trost Context triple: [Brandon Trost, familyName, Trost]
-
A.
Trost
chosen
Trost is a surname most notably associated with Barry M. Trost, an influential American chemist known for his work in organic synthesis and the concept of atom economy.
-
B.
Truhitte
Truhitte is a surname most notably associated with American actor and singer Daniel Truhitte, known for his role as Rolfe in the film "The Sound of Music."
-
C.
Troost
Troost is a German surname most notably associated with Paul Troost, an influential early 20th-century architect.
-
D.
Trauen
Trauen is a village in Lower Saxony, Germany, known for hosting a research facility of the German Aerospace Center (DLR).
-
E.
Tuchlauben
Tuchlauben is a historic street in Vienna’s city center, known for its upscale shops and proximity to major landmarks in the old town.
- 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_69d85a1355608190a6673ddb67231d54 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e2a8e88819093e4b7479b2c80cd |
completed | April 16, 2026, 1:40 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff01ff42d48190897e6653d2b4f8a4 |
completed | May 9, 2026, 9:44 a.m. |
Created at: April 10, 2026, 3:17 a.m.