Triple
T3777094
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | PAW Patrol: The Movie |
E83332
|
entity |
| Predicate | setIn |
P1393
|
FINISHED |
| Object |
Adventure City
Adventure City is the bustling, high-tech metropolis that serves as the primary urban setting in the animated film "PAW Patrol: The Movie."
|
E387378
|
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: Adventure City | Statement: [PAW Patrol: The Movie, setIn, Adventure City]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Adventure City Context triple: [PAW Patrol: The Movie, setIn, Adventure City]
-
A.
Winter City
Winter City is the popular nickname for Östersund, a Swedish town renowned for its cold climate and strong winter sports culture.
-
B.
Golden City
Golden City is the popular nickname for Jaisalmer, a historic sandstone city in the Thar Desert of Rajasthan, India, famed for its golden-hued fort and architecture.
-
C.
Golden City
Golden City is a poetic nickname for Prague, highlighting the city's historic skyline of gilded spires and sunlit architecture.
-
D.
Golden City
Golden City is a small rural town in Barton County, southwestern Missouri, known for its agricultural surroundings and tight-knit community.
-
E.
Red City
Red City is a popular nickname for Marrakesh, the historic Moroccan metropolis famed for its reddish sandstone buildings and city walls.
- 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: Adventure City Triple: [PAW Patrol: The Movie, setIn, Adventure City]
Generated description
Adventure City is the bustling, high-tech metropolis that serves as the primary urban setting in the animated film "PAW Patrol: The Movie."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Adventure City Target entity description: Adventure City is the bustling, high-tech metropolis that serves as the primary urban setting in the animated film "PAW Patrol: The Movie."
-
A.
Winter City
Winter City is the popular nickname for Östersund, a Swedish town renowned for its cold climate and strong winter sports culture.
-
B.
Golden City
Golden City is the popular nickname for Jaisalmer, a historic sandstone city in the Thar Desert of Rajasthan, India, famed for its golden-hued fort and architecture.
-
C.
Golden City
Golden City is a poetic nickname for Prague, highlighting the city's historic skyline of gilded spires and sunlit architecture.
-
D.
Golden City
Golden City is a small rural town in Barton County, southwestern Missouri, known for its agricultural surroundings and tight-knit community.
-
E.
Red City
Red City is a popular nickname for Marrakesh, the historic Moroccan metropolis famed for its reddish sandstone buildings and city walls.
- 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_69ad8b235e608190b5a2b1d1bfcef50b |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adcc5d3dbc8190b6ab118a56acd5a3 |
completed | March 8, 2026, 7:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4e534a02c8190b8dd76ed965f393f |
completed | March 14, 2026, 4:33 a.m. |
| NEDg | Description generation | batch_69b4e6b1cefc8190971e9441dc145e19 |
completed | March 14, 2026, 4:40 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b4ea8b9d2c819088db1fdf9dc90c0c |
completed | March 14, 2026, 4:56 a.m. |
Created at: March 8, 2026, 3:36 p.m.