Triple
T1162639
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Daimler-Benz DB 601 |
E24527
|
entity |
| Predicate | manufacturer |
P490
|
FINISHED |
| Object | Daimler-Benz |
E88466
|
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: Daimler-Benz | Statement: [Daimler-Benz DB 601, manufacturer, Daimler-Benz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Daimler-Benz Context triple: [Daimler-Benz DB 601, manufacturer, Daimler-Benz]
-
A.
Daimler AG
chosen
Daimler AG was a major German multinational automotive corporation best known as the longtime manufacturer and corporate parent behind the Mercedes-Benz brand.
-
B.
Mercedes-Benz
Mercedes-Benz is a German luxury automobile manufacturer renowned for its premium cars, engineering innovation, and iconic three-pointed star logo.
-
C.
Volkswagen Group
Volkswagen Group is a major German multinational automotive manufacturer that owns brands such as Volkswagen, Audi, Porsche, and Škoda and is one of the largest car producers in the world.
-
D.
Borsigwerke
Borsigwerke is a Berlin U-Bahn station on line U6 serving the Tegel district in the city’s northwest.
-
E.
Mercedes
Mercedes is a courageous and compassionate housekeeper who secretly aids the Spanish Maquis resistance in Guillermo del Toro’s dark fantasy film "Pan’s Labyrinth."
- 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_69a494060e148190abb42f971242c197 |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bcb2bb84819088bd94e91c10fb0c |
completed | March 1, 2026, 10:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac66803e0881908d2eea76dad028fa |
completed | March 7, 2026, 5:55 p.m. |
Created at: March 1, 2026, 7:45 p.m.