Triple
T8552245
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Magician Lord |
E202470
|
entity |
| Predicate | developer |
P73
|
FINISHED |
| Object |
Alpha Denshi
Alpha Denshi was a Japanese video game company best known for developing early arcade and Neo Geo titles before later becoming ADK.
|
E741496
|
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: Alpha Denshi | Statement: [Magician Lord, developer, Alpha Denshi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Alpha Denshi Context triple: [Magician Lord, developer, Alpha Denshi]
-
A.
Matsuda Force
Matsuda Force is a Japanese military unit featured as an opposing force in the strategy video game "Operation Backhander."
-
B.
Shinkiari
Shinkiari is a town in Pakistan’s Khyber Pakhtunkhwa province, known for its agricultural surroundings and its location along the Karakoram Highway near Mansehra.
-
C.
Tokusuke
Tokusuke is the given name of Nakae Chōmin, a prominent Japanese political theorist, journalist, and early advocate of liberal democracy in the Meiji era.
-
D.
Tani Tateki
Tani Tateki was a Japanese samurai and military commander of the Meiji era who played a key role in government forces during the Satsuma Rebellion.
-
E.
Kodenmachō
Kodenmachō is a neighborhood in Chūō ward, central Tokyo, known as a traditional commercial district with a mix of small businesses, offices, and residential buildings.
- 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: Alpha Denshi Triple: [Magician Lord, developer, Alpha Denshi]
Generated description
Alpha Denshi was a Japanese video game company best known for developing early arcade and Neo Geo titles before later becoming ADK.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Alpha Denshi Target entity description: Alpha Denshi was a Japanese video game company best known for developing early arcade and Neo Geo titles before later becoming ADK.
-
A.
Matsuda Force
Matsuda Force is a Japanese military unit featured as an opposing force in the strategy video game "Operation Backhander."
-
B.
Shinkiari
Shinkiari is a town in Pakistan’s Khyber Pakhtunkhwa province, known for its agricultural surroundings and its location along the Karakoram Highway near Mansehra.
-
C.
Tokusuke
Tokusuke is the given name of Nakae Chōmin, a prominent Japanese political theorist, journalist, and early advocate of liberal democracy in the Meiji era.
-
D.
Tani Tateki
Tani Tateki was a Japanese samurai and military commander of the Meiji era who played a key role in government forces during the Satsuma Rebellion.
-
E.
Kodenmachō
Kodenmachō is a neighborhood in Chūō ward, central Tokyo, known as a traditional commercial district with a mix of small businesses, offices, and residential buildings.
- 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_69ca832610e08190b3b6c6cd2c250255 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe8882704819094b688d46169433a |
completed | March 31, 2026, 3:30 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce6dc7f6fc8190addd5d2bbe1f4408 |
completed | April 2, 2026, 1:23 p.m. |
| NEDg | Description generation | batch_69ce6f3f40708190a351600ec9f12ee4 |
completed | April 2, 2026, 1:29 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ce703b74f8819093bda2d3e59f7e94 |
completed | April 2, 2026, 1:33 p.m. |
Created at: March 30, 2026, 6:19 p.m.