Triple
T10174859
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Adam Krafft |
E235824
|
entity |
| Predicate | placeOfDeath |
P21
|
FINISHED |
| Object | Schwaz |
E500192
|
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: Schwaz | Statement: [Adam Krafft, placeOfDeath, Schwaz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Schwaz Context triple: [Adam Krafft, placeOfDeath, Schwaz]
-
A.
Schwaz
chosen
Schwaz is a historic silver-mining town in the Austrian state of Tyrol, known for its medieval center and alpine setting.
-
B.
Schwarz
Schwarz is a theoretical physicist best known as one of the pioneers of string theory and for his work on anomaly cancellation.
-
C.
Schwarz
Schwarz is a common German surname borne by numerous notable individuals across fields such as science, politics, and the arts.
-
D.
Swart
Swart is a surname of Afrikaans and Dutch origin, notably borne by Charles Robberts Swart, the first State President of South Africa.
-
E.
Blau
The Blau is a small river in the German state of Baden-Württemberg that flows through the city of Blaustein before joining the Danube.
- 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_69ca84d1d5f88190ab878a1021ecff68 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdecd26a8c8190a391b9d5e47ebb72 |
completed | April 2, 2026, 4:13 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d3011742b48190bc8b8b6ba03c32b0 |
completed | April 6, 2026, 12:40 a.m. |
Created at: March 30, 2026, 9:11 p.m.