Triple
T13227643
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bertha Benz |
E314922
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Benz |
E11202
|
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: Benz | Statement: [Bertha Benz, familyName, Benz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Benz Context triple: [Bertha Benz, familyName, Benz]
-
A.
Mobil
Mobil is a major American oil company and fuel brand that became part of ExxonMobil after a 1999 merger.
-
B.
Spragga Benz
Spragga Benz is a prominent Jamaican dancehall deejay known for his influential 1990s hits and collaborations across reggae, hip hop, and international pop music.
-
C.
Benz Velo
The Benz Velo was one of the world’s first production automobiles, a lightweight, mass-produced car introduced by the German manufacturer Benz & Cie. in the late 19th century.
-
D.
Mercedes-Benz
chosen
Mercedes-Benz is a German luxury automobile manufacturer renowned for its premium cars, engineering innovation, and iconic three-pointed star logo.
-
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_69d806affc688190a25b6ccc588e9c72 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98d3232d48190a3c792b025c596a6 |
completed | April 10, 2026, 11:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6ff2a4b0c8190a853a1f6f4d1cbaf |
completed | May 3, 2026, 7:54 a.m. |
Created at: April 9, 2026, 9:21 p.m.