Triple
T8244540
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Trucks (1997 film) |
E192817
|
entity |
| Predicate | productionCompany |
P490
|
FINISHED |
| Object |
Allegro Films
Allegro Films is a film production company known for producing feature films such as the 1997 movie "Trucks."
|
E721817
|
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: Allegro Films | Statement: [Trucks (1997 film), productionCompany, Allegro Films]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Allegro Films Context triple: [Trucks (1997 film), productionCompany, Allegro Films]
-
A.
Eldorado Films
Eldorado Films is a film production company best known for its involvement in the 1984 adventure romantic comedy "Romancing the Stone."
-
B.
Minerva Film
Minerva Film is an Italian film distribution and production company known for handling classic and auteur cinema releases.
-
C.
Skreba Films
Skreba Films is a film production company known for producing the biographical drama "Tom & Viv."
-
D.
Eagle-Lion Films
Eagle-Lion Films was an American film production and distribution company active in the late 1940s, best known for its low-budget features and notable film noir titles.
-
E.
Carnival Films
Carnival Films is a British television and film production company best known internationally for creating the period drama series "Downton Abbey."
- 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: Allegro Films Triple: [Trucks (1997 film), productionCompany, Allegro Films]
Generated description
Allegro Films is a film production company known for producing feature films such as the 1997 movie "Trucks."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Allegro Films Target entity description: Allegro Films is a film production company known for producing feature films such as the 1997 movie "Trucks."
-
A.
Eldorado Films
Eldorado Films is a film production company best known for its involvement in the 1984 adventure romantic comedy "Romancing the Stone."
-
B.
Minerva Film
Minerva Film is an Italian film distribution and production company known for handling classic and auteur cinema releases.
-
C.
Skreba Films
Skreba Films is a film production company known for producing the biographical drama "Tom & Viv."
-
D.
Eagle-Lion Films
Eagle-Lion Films was an American film production and distribution company active in the late 1940s, best known for its low-budget features and notable film noir titles.
-
E.
Carnival Films
Carnival Films is a British television and film production company best known internationally for creating the period drama series "Downton Abbey."
- 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_69ca82de7b8c81908d8106f8a53cff9b |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb78711f5081909c2f357334491a07 |
completed | March 31, 2026, 7:32 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cd352b1a288190bd13ef84bef7fa1c |
completed | April 1, 2026, 3:09 p.m. |
| NEDg | Description generation | batch_69cd36ef47e88190ae96ea2459552247 |
completed | April 1, 2026, 3:17 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69cd4edfda788190a29f5d9a7a61f6ed |
completed | April 1, 2026, 4:59 p.m. |
Created at: March 30, 2026, 5:47 p.m.