Triple
T22485726
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Space Wrangler |
E555871
|
entity |
| Predicate | hasTrack |
P3284
|
FINISHED |
| Object | 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: Machine | Statement: [Space Wrangler, hasTrack, Machine]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Machine Context triple: [Space Wrangler, hasTrack, Machine]
-
A.
Machine
chosen
Machine is a professional ultimate frisbee team based in Chicago, Illinois, competing at the elite club level in USA Ultimate competitions.
-
B.
Machines
The Machines are a powerful, sentient artificial intelligence civilization that rules over humanity and the simulated reality in the Matrix franchise.
-
C.
G-machine
The G-machine is an abstract machine designed to efficiently implement non-strict functional languages like Haskell by compiling programs into graph reduction operations.
-
D.
the Machine
The Machine is a notorious torture device from "The Princess Bride" that painfully drains years of life from its victims.
-
E.
Maquinna
Maquinna was a prominent 18th–19th century Nuu-chah-nulth chief known for his influential role in early contacts and trade with European explorers on the Pacific Northwest Coast.
- 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_69e11e53897c819088863779f8c50bb0 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15c3c6d808190b6dc70c3d1985bf3 |
completed | April 29, 2026, 1:17 a.m. |
Created at: April 16, 2026, 8:49 p.m.