Triple
T22591345
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Margarete Steiff |
E564956
|
entity |
| Predicate | founded |
P104
|
FINISHED |
| Object | Steiff |
—
|
NE NERFINISHED |
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: Steiff | Statement: [Margarete Steiff, founded, Steiff]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Steiff Context triple: [Margarete Steiff, founded, Steiff]
-
A.
Steiff
Steiff is a renowned German toy company best known for inventing the modern teddy bear and producing high-quality collectible stuffed animals.
-
B.
Margarete Steiff GmbH
chosen
Margarete Steiff GmbH is a German toy company famous worldwide for inventing the modern teddy bear and producing high-quality plush animals.
-
C.
Teddies
Teddies is the informal nickname commonly used for St Edward's School, a co-educational independent boarding school in Oxford, England.
-
D.
Bundy Bear
Bundy Bear is an Australian beer brand mascot, best known as the laid-back polar bear character featured in Bundaberg Rum advertisements.
-
E.
Stanley
Stanley is the given first name of Ann Dunham, the American anthropologist and mother of former U.S. President Barack Obama.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e245836014819091b91ed3074742a3 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f16160651081909d23735336fd7a16 |
completed | April 29, 2026, 1:39 a.m. |
Created at: April 17, 2026, 2:48 p.m.