Triple
T17880542
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hopscotch |
E447070
|
entity |
| Predicate | productionCompany |
P490
|
FINISHED |
| Object |
MLD Films
MLD Films is a film production company known for collaborating with other studios, such as Hopscotch, to develop and produce motion picture projects.
|
E1293222
|
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: MLD Films | Statement: [Hopscotch, productionCompany, MLD Films]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MLD Films Context triple: [Hopscotch, productionCompany, MLD Films]
-
A.
MLR Films
MLR Films is a film production company known for producing the 1981 crime drama "Fort Apache, The Bronx."
-
B.
M6 Films
M6 Films is a French film production company known for backing popular international action and thriller movies.
-
C.
Mint Films
Mint Films is an independent record label known for releasing music by the American rock band Mercury Rev.
-
D.
Cinelou Films
Cinelou Films is an independent American film production company known for producing character-driven dramas such as the 2014 film "Cake."
-
E.
Integral Films
Integral Films is a film production company known for working on projects such as David Cronenberg’s satirical drama "Maps to the Stars."
- 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: MLD Films Triple: [Hopscotch, productionCompany, MLD Films]
Generated description
MLD Films is a film production company known for collaborating with other studios, such as Hopscotch, to develop and produce motion picture projects.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: MLD Films Target entity description: MLD Films is a film production company known for collaborating with other studios, such as Hopscotch, to develop and produce motion picture projects.
-
A.
MLR Films
MLR Films is a film production company known for producing the 1981 crime drama "Fort Apache, The Bronx."
-
B.
M6 Films
M6 Films is a French film production company known for backing popular international action and thriller movies.
-
C.
Mint Films
Mint Films is an independent record label known for releasing music by the American rock band Mercury Rev.
-
D.
Cinelou Films
Cinelou Films is an independent American film production company known for producing character-driven dramas such as the 2014 film "Cake."
-
E.
Integral Films
Integral Films is a film production company known for working on projects such as David Cronenberg’s satirical drama "Maps to the Stars."
- 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_69d8b9f4c22c819093c2680434472894 |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e49c0e56bc819097649377b520de63 |
completed | April 19, 2026, 9:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0313d3dba88190a5dd60d1d4ac63f0 |
completed | May 12, 2026, 11:49 a.m. |
| NEDg | Description generation | batch_6a0314c062388190807c3a40f3693b89 |
completed | May 12, 2026, 11:53 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a03158595708190bdfa0391a829fbc3 |
completed | May 12, 2026, 11:56 a.m. |
Created at: April 10, 2026, 10:18 a.m.