Triple
T25900765
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mario Party 4 |
E652606
|
entity |
| Predicate | setting |
P1957
|
FINISHED |
| Object |
Party Cube
Party Cube is the whimsical, cube-shaped party world that serves as the main hub and game board environment in Mario Party 4.
|
E1699948
|
NE FINISHED |
How this triple was built (2 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: Party Cube | Statement: [Mario Party 4, setting, Party Cube]
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: Party Cube Triple: [Mario Party 4, setting, Party Cube]
Generated description
Party Cube is the whimsical, cube-shaped party world that serves as the main hub and game board environment in Mario Party 4.
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_69e7ab3c6cc081908de59bfcc28ec19d |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f6038950948190a64ecb98ebcca94b |
completed | May 2, 2026, 2 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a10ecc4459881908a9612e7ce1bd1aa |
completed | May 22, 2026, 11:54 p.m. |
| NEDg | Description generation | batch_6a10ef215b448190853f97729867b5fb |
completed | May 23, 2026, 12:04 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a10efc6a0e48190a595a5025ad5c926 |
completed | May 23, 2026, 12:07 a.m. |
Created at: April 22, 2026, 8:24 a.m.