Triple
T7664720
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MMIX |
E173597
|
entity |
| Predicate | predecessor |
P97
|
FINISHED |
| Object | MIX |
E173596
|
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: MIX | Statement: [MMIX, predecessor, MIX]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MIX Context triple: [MMIX, predecessor, MIX]
-
A.
MIX
chosen
MIX is Donald Knuth’s hypothetical computer architecture used in *The Art of Computer Programming* to illustrate and analyze algorithms in a machine-level context.
-
B.
Mixed Me!
"Mixed Me!" is a children's picture book by Taye Diggs that celebrates a biracial child's identity, confidence, and sense of self.
-
C.
In the Mix
In the Mix is a 2005 romantic comedy-crime film starring Usher as a DJ who becomes a bodyguard entangled in a mob family's affairs.
-
D.
Remix
Remix is a full-stack web framework for building fast, dynamic React applications with an emphasis on server-side rendering, nested routing, and progressive enhancement.
-
E.
MIV
MIV is a specialized market segment of Borsa Italiana dedicated to the listing and trading of investment vehicles such as closed-end funds and investment companies.
- 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_69c699562484819086752091e3164a27 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c701bfb67c81908b416802eaf0faac |
completed | March 27, 2026, 10:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c89b1fdccc8190a69b4745dc3b2347 |
completed | March 29, 2026, 3:23 a.m. |
Created at: March 27, 2026, 4 p.m.