Triple
T16854986
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bluth Company |
E409759
|
entity |
| Predicate | associatedWithCharacter |
P1481
|
FINISHED |
| Object | Tobias Fünke |
E134421
|
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: Tobias Fünke | Statement: [Bluth Company, associatedWithCharacter, Tobias Fünke]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tobias Fünke Context triple: [Bluth Company, associatedWithCharacter, Tobias Fünke]
-
A.
Tobias Fünke
chosen
Tobias Fünke is a socially awkward, aspiring actor and former analyst-therapist known for his oblivious behavior and unintentional double entendres in the television series "Arrested Development."
-
B.
Markus Häußler
Markus Häußler is a German local politician who serves as the mayor of the town of Munderkingen in Baden-Württemberg.
-
C.
Markus Häußler
Markus Häußler is a German local politician who serves as the mayor of the municipality of Illerkirchberg in Baden-Württemberg.
-
D.
Tobias Kohn
Tobias Kohn is a computer scientist and software developer known for his contributions to the Python language, including co-authoring PEP 622 on pattern matching.
-
E.
Markus Förderer
Markus Förderer is a German cinematographer known for his visually striking work on films such as Stonewall (2015), Independence Day: Resurgence, and I Origins.
- 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_69d88395e6c88190b22730f335107c14 |
completed | April 10, 2026, 4:59 a.m. |
| NER | Named-entity recognition | batch_69e3b37c6e808190975b14b228253029 |
completed | April 18, 2026, 4:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a01232992ec81909dbbd2e28111e8f4 |
completed | May 11, 2026, 12:30 a.m. |
Created at: April 10, 2026, 5:24 a.m.