Triple
T26140850
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mario Party 8 |
E659512
|
entity |
| Predicate | hasGameMode |
P10208
|
FINISHED |
| Object |
Extras Zone
Extras Zone is a bonus mode in Mario Party 8 that offers a collection of additional mini-games and special activities separate from the main party modes.
|
E1710130
|
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: Extras Zone | Statement: [Mario Party 8, hasGameMode, Extras Zone]
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: Extras Zone Triple: [Mario Party 8, hasGameMode, Extras Zone]
Generated description
Extras Zone is a bonus mode in Mario Party 8 that offers a collection of additional mini-games and special activities separate from the main party modes.
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_69ee5bc3c20c8190bf2cf272f4170e95 |
completed | April 26, 2026, 6:38 p.m. |
| NER | Named-entity recognition | batch_69f60be435b48190a389ebb5a4537a16 |
completed | May 2, 2026, 2:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a1127688c38819084905127993e3a90 |
completed | May 23, 2026, 4:04 a.m. |
| NEDg | Description generation | batch_6a112da03b68819097fd74efe58736a5 |
completed | May 23, 2026, 4:31 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a112e3c850c819094d0e20d26f0dcf3 |
completed | May 23, 2026, 4:34 a.m. |
Created at: April 26, 2026, 8:20 p.m.