Triple
T11009733
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Help! (film) |
E260215
|
entity |
| Predicate | productionCompany |
P490
|
FINISHED |
| Object |
Subafilms
Subafilms was a film production company associated with The Beatles, involved in producing several of their cinematic projects during the 1960s.
|
E899423
|
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: Subafilms | Statement: [Help! (film), productionCompany, Subafilms]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Subafilms Context triple: [Help! (film), productionCompany, Subafilms]
-
A.
Dohafilms
Dohafilms is a film production company known for helping produce the 2014 animated adaptation of Kahlil Gibran’s "The Prophet."
-
B.
Lolafilms
Lolafilms is a Spanish film production company known for backing prominent Spanish-language cinema, including acclaimed features from the 1990s and 2000s.
-
C.
MDB Films
MDB Films is a film production company known for producing the movie "The Kingdom."
-
D.
Sketch Films
Sketch Films is a television production company best known for its work on the supernatural drama series "Sleepy Hollow."
-
E.
Como-Films
Como-Films is a French film production company best known for producing Alain Resnais’s influential 1959 film "Hiroshima mon amour."
- 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: Subafilms Triple: [Help! (film), productionCompany, Subafilms]
Generated description
Subafilms was a film production company associated with The Beatles, involved in producing several of their cinematic projects during the 1960s.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Subafilms Target entity description: Subafilms was a film production company associated with The Beatles, involved in producing several of their cinematic projects during the 1960s.
-
A.
Dohafilms
Dohafilms is a film production company known for helping produce the 2014 animated adaptation of Kahlil Gibran’s "The Prophet."
-
B.
Lolafilms
Lolafilms is a Spanish film production company known for backing prominent Spanish-language cinema, including acclaimed features from the 1990s and 2000s.
-
C.
MDB Films
MDB Films is a film production company known for producing the movie "The Kingdom."
-
D.
Sketch Films
Sketch Films is a television production company best known for its work on the supernatural drama series "Sleepy Hollow."
-
E.
Como-Films
Como-Films is a French film production company best known for producing Alain Resnais’s influential 1959 film "Hiroshima mon amour."
- 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_69d6aa9687448190b28d353b1b6a610e |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d79788d44c819084f35693ed96f422 |
completed | April 9, 2026, 12:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e37498b9fc8190860acede4f49ea4a |
completed | April 18, 2026, 12:10 p.m. |
| NEDg | Description generation | batch_69e378dcc92c8190952d4acfee2a309c |
completed | April 18, 2026, 12:28 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69e37be75a588190abb9569ef1e87279 |
completed | April 18, 2026, 12:41 p.m. |
Created at: April 8, 2026, 9:25 p.m.