Triple
T10194642
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pet |
E238129
|
entity |
| Predicate | productionCompany |
P490
|
FINISHED |
| Object |
Magic Lantern
Magic Lantern is a film and television production company known for developing and producing screen content.
|
E847607
|
NE FINISHED |
How this triple was built (4 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: Magic Lantern | Statement: [Pet, productionCompany, Magic Lantern]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Magic Lantern Context triple: [Pet, productionCompany, Magic Lantern]
-
A.
Lanterna
Lanterna is the iconic historic lighthouse of Genoa, Italy, and one of the oldest and tallest lighthouses still in operation in the world.
-
B.
Lucem Aspicio
Lucem Aspicio is the Latin motto of the University of Costa Rica, expressing its guiding ideal of seeking and embracing enlightenment or knowledge.
-
C.
The Light
The Light is a chapter or section within the novel "Like Water for Chocolate," contributing to its blend of magical realism, romance, and culinary symbolism.
-
D.
The Light
The Light is a notable work by the rapper Common, showcasing his introspective lyricism and soulful, jazz-influenced hip-hop style.
-
E.
The Light
"The Light" is a song by Sara Bareilles from her album "Kaleidoscope Heart," known for its heartfelt lyrics and piano-driven pop sound.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Magic Lantern Triple: [Pet, productionCompany, Magic Lantern]
Generated description
Magic Lantern is a film and television production company known for developing and producing screen content.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Magic Lantern Target entity description: Magic Lantern is a film and television production company known for developing and producing screen content.
-
A.
Lanterna
Lanterna is the iconic historic lighthouse of Genoa, Italy, and one of the oldest and tallest lighthouses still in operation in the world.
-
B.
Lucem Aspicio
Lucem Aspicio is the Latin motto of the University of Costa Rica, expressing its guiding ideal of seeking and embracing enlightenment or knowledge.
-
C.
The Light
The Light is a notable work by the rapper Common, showcasing his introspective lyricism and soulful, jazz-influenced hip-hop style.
-
D.
The Light
The Light is a chapter or section within the novel "Like Water for Chocolate," contributing to its blend of magical realism, romance, and culinary symbolism.
-
E.
The Light
The Light is a work by author W. Jeffrey, likely a novel or story centered on themes of illumination, revelation, or spiritual insight.
- F. None of above. chosen
Provenance (5 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_69ca84de1b208190bf17bb305b002605 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdedc7cc748190bceb8f657afcc054 |
completed | April 2, 2026, 4:17 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d317dbfb7c819087aafc7161b14707 |
completed | April 6, 2026, 2:18 a.m. |
| NEDg | Description generation | batch_69d319670c6c8190b77257340ec8e6d4 |
completed | April 6, 2026, 2:24 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d31d371e948190ac6d31daad2afbdf |
completed | April 6, 2026, 2:40 a.m. |
Created at: March 30, 2026, 9:13 p.m.