Triple
T14415276
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nokia 8310 |
E357433
|
entity |
| Predicate | includesGame |
P1393
|
FINISHED |
| Object | Space Impact |
E996347
|
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: Space Impact | Statement: [Nokia 8310, includesGame, Space Impact]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Space Impact Context triple: [Nokia 8310, includesGame, Space Impact]
-
A.
Space Impact
chosen
Space Impact is a classic side-scrolling shoot 'em up mobile game best known for its popularity on early Nokia phones, where players controlled a spaceship battling waves of enemies and bosses.
-
B.
Space
"Space" is a 1982 epic historical novel by James A. Michener that explores the development of the U.S. space program and the people involved in it.
-
C.
Space
Space is a British television channel known for broadcasting science fiction and genre programming, including episodes of Doctor Who.
-
D.
Space
Space is JetBrains’ integrated team collaboration and development platform that combines source code hosting, project management, communication tools, and CI/CD in a single environment.
-
E.
Spaces
Spaces is a virtual desktop feature in macOS that lets users organize and switch between multiple workspaces to manage open applications and windows more efficiently.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d82793421c8190861eb0e673b085de |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de90cc99208190a2313b1acfb5d802 |
completed | April 14, 2026, 7:09 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd552a75ec8190b966d509d315ca60 |
completed | May 8, 2026, 3:14 a.m. |
Created at: April 10, 2026, 1:17 a.m.