Triple
T9967678
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Trinity |
E195725
|
entity |
| Predicate | enemyOf |
P437
|
FINISHED |
| Object | The Machines |
E832014
|
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: The Machines | Statement: [Trinity, enemyOf, The Machines]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: The Machines Context triple: [Trinity, enemyOf, The Machines]
-
A.
the Machines
chosen
The Machines are the highly advanced artificial intelligences that dominate and enslave humanity in the Matrix film series.
-
B.
The Machine
The Machine is the nickname of Albert Pujols, a Dominican-American former Major League Baseball first baseman renowned for his remarkably consistent and powerful hitting.
-
C.
The Machine
The Machine is a powerful, clandestine artificial superintelligence from the TV series "Person of Interest" that predicts violent crimes by analyzing global surveillance data.
-
D.
Dream Machines
Dream Machines is the visionary second half of Ted Nelson’s influential 1974 book that imagines interactive, hypertext-based computers as tools for personal creativity and liberation.
-
E.
Machina
Machina is a local government area and town in northeastern Nigeria’s Yobe State, near the border with Niger.
- 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_69ca82ebd1288190912f9e4482d1fa35 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cdb71f9d7c8190ac02c53052c1c6ad |
completed | April 2, 2026, 12:23 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d269fc0d20819082bfe0331972e2b6 |
completed | April 5, 2026, 1:56 p.m. |
Created at: March 30, 2026, 8:47 p.m.