Triple
T23411790
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Carlos |
E560087
|
entity |
| Predicate | originalNetwork |
P2594
|
FINISHED |
| Object | Arte |
—
|
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: Arte | Statement: [Carlos, originalNetwork, Arte]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Arte Context triple: [Carlos, originalNetwork, Arte]
-
A.
Arte
chosen
Arte is a European public-service television network known for its high-quality cultural, artistic, and documentary programming, jointly funded and operated by France and Germany.
-
B.
ART
ART is the managed runtime environment used by the Android operating system to execute applications, providing ahead-of-time and just-in-time compilation, garbage collection, and other core execution services.
-
C.
ART
ART is the commonly used abbreviation for the Artland Dragons, a professional basketball team based in Quakenbrück, Germany.
-
D.
ART
ART is the bus rapid transit system serving Albuquerque, New Mexico, designed to provide faster and more efficient public transportation along key corridors in the city.
-
E.
ART
ART is a renowned professional theater company based in Cambridge, Massachusetts, known for its innovative and experimental productions and its affiliation with Harvard University.
- 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.