Triple
T18206358
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | World State |
E435912
|
entity |
| Predicate | caste |
P16727
|
FINISHED |
| Object | Epsilon |
—
|
NE NERFINISHED |
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: Epsilon | Statement: [World State, caste, Epsilon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Epsilon Context triple: [World State, caste, Epsilon]
-
A.
Epsilon
Epsilon is a Japanese solid-fuel orbital launch vehicle developed by JAXA for launching small satellites.
-
B.
Epsilon
Epsilon is the fifth letter of the Greek alphabet, commonly used in mathematics and science to denote small quantities or error terms.
-
C.
Epsilon
Epsilon is a programmable text editor similar to Emacs, known for its powerful customization features and support for multiple programming languages.
-
D.
Epsilon
Epsilon is a major marketing and data analytics company known for its customer relationship management, data-driven marketing solutions, and digital advertising services.
-
E.
Epsilon I
Epsilon I is an automotive platform developed by General Motors for front-wheel-drive and all-wheel-drive mid-size vehicles.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide. chosen
Provenance (2 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_69d8b90dba6481908e119eb9aa4ca0cb |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4e2234b988190bbe2c2164d61f65f |
completed | April 19, 2026, 2:09 p.m. |
Created at: April 10, 2026, 10:32 a.m.