Triple
T1771382
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Würzburg radar |
E38881
|
entity |
| Predicate | developedBy |
P73
|
FINISHED |
| Object | Telefunken |
E91046
|
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: Telefunken | Statement: [Würzburg radar, developedBy, Telefunken]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Telefunken Context triple: [Würzburg radar, developedBy, Telefunken]
-
A.
Telefunken
chosen
Telefunken is a historic German electronics and television brand known for its radios, audio equipment, and consumer electronics.
-
B.
Fitel
Fitel was a financial technology startup where Jeff Bezos worked early in his career, before joining D. E. Shaw and later founding Amazon.
-
C.
Kenwood
Kenwood is a small community in California’s Sonoma Valley known for its wineries, vineyards, and scenic rural charm.
-
D.
Kenwood
Kenwood is a historic neighborhood within Dracut, Massachusetts, known for its preserved architecture and local heritage.
-
E.
Boxtel
Boxtel is a town and municipality in the southern Netherlands known for its historic center and location between the cities of Eindhoven and ’s-Hertogenbosch.
- 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_69a8862e61708190af97b9838cc3f5de |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69aa648fe908819098fd27b74b17fabb |
completed | March 6, 2026, 5:22 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ada995dab48190b7efcf1007fc9d5f |
completed | March 8, 2026, 4:53 p.m. |
Created at: March 4, 2026, 7:31 p.m.