Triple
T7977105
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stewart Butterfield |
E185473
|
entity |
| Predicate | employer |
P7
|
FINISHED |
| Object | Ludicorp |
E703155
|
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: Ludicorp | Statement: [Stewart Butterfield, employer, Ludicorp]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ludicorp Context triple: [Stewart Butterfield, employer, Ludicorp]
-
A.
Ludicorp
chosen
Ludicorp was a Canadian software company best known for creating the photo-sharing service Flickr before being acquired by Yahoo.
-
B.
Creatures Inc.
Creatures Inc. is a Japanese video game development company best known for its key role in creating and managing the Pokémon franchise’s games, cards, and related media.
-
C.
Kopelson Entertainment
Kopelson Entertainment is a film and television production company best known for producing high-profile Hollywood action and thriller movies.
-
D.
Wolf Entertainment
Wolf Entertainment is an American television production company founded by producer Dick Wolf, best known for creating and overseeing the long-running Law & Order and Chicago franchise series.
-
E.
Chameleon Entertainment
Chameleon Entertainment is a music record label known for producing and distributing recordings for various artists across genres.
- 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_69ca829851908190b4e03829353ee7c3 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3bf716508190b4245bd5d89ae8c4 |
completed | March 31, 2026, 3:13 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cc5677968881908835169157244962 |
completed | March 31, 2026, 11:19 p.m. |
Created at: March 30, 2026, 5:14 p.m.