Triple
T6667374
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | La Máquina |
E151637
|
entity |
| Predicate | meaning |
P129
|
FINISHED |
| Object | The Machine |
E407862
|
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 Machine | Statement: [La Máquina, meaning, The Machine]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: The Machine Context triple: [La Máquina, meaning, The Machine]
-
A.
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.
-
B.
The Machine
chosen
The Machine is a powerful, clandestine artificial superintelligence from the TV series "Person of Interest" that predicts violent crimes by analyzing global surveillance data.
-
C.
La Máquina
La Máquina is the popular nickname of Mexican football club Cruz Azul, highlighting its reputation as a powerful, relentless team.
-
D.
The Machine of the World
The Machine of the World is a famous allegorical vision in Luís de Camões’ epic poem *Os Lusíadas*, in which the cosmos and its secrets are revealed to the Portuguese explorers.
-
E.
Man and Machine
"Man and Machine" is a key chapter in Peter Thiel’s book "Zero to One" that explores how humans and computers can best complement each other in creating innovative, future-defining technologies.
- 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_69c687f71fc081909dbd45d6377f6045 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6b09ec2ec8190aa666c68c6c2cfc6 |
completed | March 27, 2026, 4:30 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6ef109f5c8190aa28b5d7aa192e6e |
completed | March 27, 2026, 8:56 p.m. |
Created at: March 27, 2026, 2:02 p.m.