Triple
T18879264
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Caity Lotz |
E461777
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | The Machine |
—
|
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: The Machine | Statement: [Caity Lotz, notableWork, The Machine]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: The Machine Context triple: [Caity Lotz, notableWork, 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.
The Machine
The Machine is the sadistic, masked pornographer and primary antagonist in the 1999 crime thriller film "8MM."
-
D.
The Machine
The Machine is the nickname of Shelly Levene, a once-legendary but now struggling real estate salesman in David Mamet’s play and film "Glengarry Glen Ross."
-
E.
the Machine
The Machine is a notorious torture device from "The Princess Bride" that painfully drains years of life from its victims.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d8dcfc3430819095ee6fc0eb4c06a5 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5c3d06ef481908bba297d7a1fd011 |
completed | April 20, 2026, 6:12 a.m. |
Created at: April 10, 2026, 11:57 a.m.