Triple
T23411799
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Carlos |
E560087
|
entity |
| Predicate | productionCompany |
P490
|
FINISHED |
| Object | Egoli Tossell Film |
—
|
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: Egoli Tossell Film | Statement: [Carlos, productionCompany, Egoli Tossell Film]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Egoli Tossell Film Context triple: [Carlos, productionCompany, Egoli Tossell Film]
-
A.
Egoli Tossell Film
chosen
Egoli Tossell Film is a German film production company known for producing a range of international and European feature films and co-productions.
-
B.
Galavis Film
Galavis Film is a film production company known for working on international action-thriller projects such as "The Cold Light of Day."
-
C.
Teitler Film
Teitler Film is a film production company known for producing feature films such as the family sci-fi adventure "Zathura: A Space Adventure."
-
D.
Lea Film
Lea Film was an Italian film production company active during the mid-20th century, known for contributing to genre cinema including giallo and thriller films.
-
E.
Geria Film
Geria Film is a film production company known for producing the movie "Fedora."
- 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_69e2454b3a5881909c64773dc8a5d289 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f1a51183bc8190bd4860607b26b4b2 |
completed | April 29, 2026, 6:28 a.m. |
Created at: April 17, 2026, 5:38 p.m.