Triple
T13716684
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Two Women |
E328918
|
entity |
| Predicate | distributor |
P1951
|
FINISHED |
| Object |
Paradise
Paradise is a film distribution company known for handling the release of the movie "Two Women."
|
E1062338
|
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: Paradise | Statement: [Two Women, distributor, Paradise]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Paradise Context triple: [Two Women, distributor, Paradise]
-
A.
Paradise
Paradise is a popular high-elevation area on the south slope of Mount Rainier known for its spectacular wildflower meadows, hiking trails, and panoramic mountain views.
-
B.
Paradise
Paradise is the eternal, blissful abode in the hereafter promised by Allah to the righteous in Islamic belief.
-
C.
Paradise
Paradise is a photographic series by German artist Thomas Struth that features large-scale, detailed images of lush, unspoiled natural landscapes.
-
D.
Paradise
"Paradise" is a popular song composed by Nacio Herb Brown, known for its classic Tin Pan Alley style and enduring presence in early American popular music.
-
E.
Paradise
"Paradise" is a critically acclaimed novel by Nobel Prize–winning author Abdulrazak Gurnah that explores colonialism, displacement, and coming-of-age in early 20th-century East Africa.
- 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: Paradise Triple: [Two Women, distributor, Paradise]
Generated description
Paradise is a film distribution company known for handling the release of the movie "Two Women."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Paradise Target entity description: Paradise is a film distribution company known for handling the release of the movie "Two Women."
-
A.
Paradise
Paradise is a 2013 comedy-drama film written and directed by Diablo Cody, marking her directorial debut and following a sheltered young woman who radically changes her life after surviving a plane crash.
-
B.
Paradise
Paradise is a fictional location in the DC Comics universe, most famously associated with Wonder Woman’s Amazonian homeland, Themyscira.
-
C.
Paradise
"Paradise" is a 1997 novel by Nobel Prize–winning author Toni Morrison that explores race, gender, community, and violence in an all-Black town in Oklahoma.
-
D.
Paradise
Paradise is a suburban town on the Avalon Peninsula of Newfoundland and Labrador, Canada, known for its rapid growth and proximity to the provincial capital, St. John’s.
-
E.
Paradise
Paradise is a section of the post-apocalyptic science fiction novel "The Rising," depicting a seemingly idyllic but ultimately perilous refuge within its dystopian world.
- 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_69d80770b9bc81909f70c8c317d53cff |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dd4398f0448190810c840a82228706 |
completed | April 13, 2026, 7:27 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7b0676e50819085fe48f86c0f93d8 |
completed | May 3, 2026, 8:30 p.m. |
| NEDg | Description generation | batch_69f7b208e3c88190962a5ce45aecf3e6 |
completed | May 3, 2026, 8:37 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f7b2c55e188190b0ea8fa400ff2dfc |
completed | May 3, 2026, 8:40 p.m. |
Created at: April 9, 2026, 9:54 p.m.