Triple
T15403060
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Serguei Mourachov |
E368373
|
entity |
| Predicate | employer |
P7
|
FINISHED |
| Object | Tiny Speck |
E703156
|
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: Tiny Speck | Statement: [Serguei Mourachov, employer, Tiny Speck]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tiny Speck Context triple: [Serguei Mourachov, employer, Tiny Speck]
-
A.
Tiny Speck
chosen
Tiny Speck was a startup best known for developing the online game Glitch before pivoting to create the workplace communication platform that became Slack.
-
B.
Little Planet
Little Planet is a mysterious, time-warping celestial body that serves as the primary location in the video game Sonic CD.
-
C.
Microcosmos
Microcosmos is a popular science book by Lynn Margulis and Dorion Sagan that explores the central role of microbes and symbiosis in the evolution and functioning of life on Earth.
-
D.
Little Obelia
Little Obelia is a classic Australian children's book by May Gibbs, featuring imaginative bush fairy characters and whimsical adventures in the natural world.
-
E.
Minimundus
Minimundus is a miniature park in Klagenfurt, Austria, featuring detailed scale models of famous buildings and landmarks from around the world.
- 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_69d85a16c68c819099c1b547fbc87b32 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e8ea0ac8190a5c68b1951ad3db1 |
completed | April 16, 2026, 1:42 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff1a716248819094fd8b205cc2a3f2 |
completed | May 9, 2026, 11:28 a.m. |
Created at: April 10, 2026, 3:19 a.m.