Triple
T10394486
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Snowman (2017 film) |
E244974
|
entity |
| Predicate | productionCompany |
P490
|
FINISHED |
| Object |
Another Park Film
Another Park Film is a film production company known for its involvement in the making of the 2017 crime thriller "The Snowman."
|
E859495
|
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: Another Park Film | Statement: [The Snowman (2017 film), productionCompany, Another Park Film]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Another Park Film Context triple: [The Snowman (2017 film), productionCompany, Another Park Film]
-
A.
In the Park
"In the Park" is a song featured on the album *Subterranean Jungle* by the American punk rock band Ramones.
-
B.
Monster Park
Monster Park was the corporate-sponsored name used for San Francisco's historic Candlestick Park stadium during the mid-2000s.
-
C.
Noites do Parque
Noites do Parque is a major nighttime concert and entertainment series held during Coimbra’s Queima das Fitas academic festival in Portugal.
-
D.
Home Park
Home Park is a historic royal deer park and landscaped estate surrounding Windsor Castle in Berkshire, England.
-
E.
Home Park
Home Park is a historic royal deer park surrounding Hampton Court Palace in southwest London, known for its expansive lawns, wildlife, and formal landscapes.
- 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: Another Park Film Triple: [The Snowman (2017 film), productionCompany, Another Park Film]
Generated description
Another Park Film is a film production company known for its involvement in the making of the 2017 crime thriller "The Snowman."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Another Park Film Target entity description: Another Park Film is a film production company known for its involvement in the making of the 2017 crime thriller "The Snowman."
-
A.
In the Park
"In the Park" is a song featured on the album *Subterranean Jungle* by the American punk rock band Ramones.
-
B.
Monster Park
Monster Park was the corporate-sponsored name used for San Francisco's historic Candlestick Park stadium during the mid-2000s.
-
C.
Noites do Parque
Noites do Parque is a major nighttime concert and entertainment series held during Coimbra’s Queima das Fitas academic festival in Portugal.
-
D.
Home Park
Home Park is a historic royal deer park and landscaped estate surrounding Windsor Castle in Berkshire, England.
-
E.
Home Park
Home Park is a historic royal deer park surrounding Hampton Court Palace in southwest London, known for its expansive lawns, wildlife, and formal landscapes.
- 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_69d381b5116081908d85227bab6d3c0c |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4e9b795fc8190aa50ce3c7360ff83 |
completed | April 7, 2026, 11:25 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d795c8271c81908a6b67822050c06d |
completed | April 9, 2026, 12:04 p.m. |
| NEDg | Description generation | batch_69d7975308648190af421c90bd1200b7 |
completed | April 9, 2026, 12:10 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d798e6721c81909647d27ce0aa615a |
completed | April 9, 2026, 12:17 p.m. |
Created at: April 6, 2026, 12:06 p.m.