Triple
T19520147
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Transformers: Armada |
E488380
|
entity |
| Predicate | productionCompany |
P490
|
FINISHED |
| Object | Gonzo |
—
|
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: Gonzo | Statement: [Transformers: Armada, productionCompany, Gonzo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gonzo Context triple: [Transformers: Armada, productionCompany, Gonzo]
-
A.
Gonzo
Gonzo is a high-altitude Gulfstream IV-SP jet operated by NOAA for atmospheric research and hurricane reconnaissance missions.
-
B.
Gonzo
chosen
Gonzo is a Japanese animation studio known for producing a wide range of anime series and films, often featuring distinctive visual styles and experimental storytelling.
-
C.
Gonzo the Great
Gonzo the Great is a daredevil, eccentric blue Muppet known for his bizarre stunts and offbeat sense of humor in The Muppet Show franchise.
-
D.
Dr. Gonzo
Dr. Gonzo is the wild, unpredictable attorney and drug-fueled companion of Raoul Duke in Hunter S. Thompson’s "Fear and Loathing in Las Vegas."
-
E.
Dr. Gonzo
Dr. Gonzo is a high-energy electro-house track by Italian DJ duo Crookers, known for its heavy bass, distorted synths, and club-oriented sound.
- 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_69d8e8da8bec819081f400199491ccc3 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e6359feb808190ba94563831adc720 |
completed | April 20, 2026, 2:18 p.m. |
Created at: April 10, 2026, 1:40 p.m.