Triple
T8577590
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jon Davison |
E203085
|
entity |
| Predicate | employer |
P7
|
FINISHED |
| Object |
1UP
1UP was a popular video game website and online community known for its news, reviews, podcasts, and editorial coverage of the gaming industry.
|
E743732
|
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: 1UP | Statement: [Jon Davison, employer, 1UP]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 1UP Context triple: [Jon Davison, employer, 1UP]
-
A.
Comix Zone
Comix Zone is a 1995 beat 'em up video game by Sega known for its distinctive comic book panel art style and meta-narrative gameplay.
-
B.
Smash
Smash is an American musical drama television series that follows the creation of a Broadway show about Marilyn Monroe, featuring Jennifer Hudson in a prominent role.
-
C.
Smash
Smash is a 1994 punk rock album by The Offspring that became a breakthrough commercial success and a defining record of 1990s punk.
-
D.
Taitō
Taitō is a special ward in central Tokyo known for its historic districts, traditional temples, and major cultural attractions such as Ueno Park and Asakusa.
-
E.
Uno
Uno is a popular shedding-type card game in which players race to discard all their cards by matching colors or numbers and using special action cards.
- 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: 1UP Triple: [Jon Davison, employer, 1UP]
Generated description
1UP was a popular video game website and online community known for its news, reviews, podcasts, and editorial coverage of the gaming industry.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: 1UP Target entity description: 1UP was a popular video game website and online community known for its news, reviews, podcasts, and editorial coverage of the gaming industry.
-
A.
Comix Zone
Comix Zone is a 1995 beat 'em up video game by Sega known for its distinctive comic book panel art style and meta-narrative gameplay.
-
B.
Smash
Smash is an American musical drama television series that follows the creation of a Broadway show about Marilyn Monroe, featuring Jennifer Hudson in a prominent role.
-
C.
Smash
Smash is a 1994 punk rock album by The Offspring that became a breakthrough commercial success and a defining record of 1990s punk.
-
D.
Taitō
Taitō is a special ward in central Tokyo known for its historic districts, traditional temples, and major cultural attractions such as Ueno Park and Asakusa.
-
E.
Uno
Uno is a popular shedding-type card game in which players race to discard all their cards by matching colors or numbers and using special action cards.
- 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_69ca8328ebe481909a8c038fa79959b4 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbea989bec81909b8c8b4af7c568ff |
completed | March 31, 2026, 3:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce899dd7d48190b44338b92ad68bd0 |
completed | April 2, 2026, 3:22 p.m. |
| NEDg | Description generation | batch_69ce8c7ad5cc8190a50c8e15ce353d1d |
completed | April 2, 2026, 3:34 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ce8d595d80819093a1b849bcb3c7c7 |
completed | April 2, 2026, 3:38 p.m. |
Created at: March 30, 2026, 6:22 p.m.