Triple
T19859377
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Skeleton Tree |
E477215
|
entity |
| Predicate | hasTrack |
P3284
|
FINISHED |
| Object | Magneto |
—
|
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: Magneto | Statement: [Skeleton Tree, hasTrack, Magneto]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Magneto Context triple: [Skeleton Tree, hasTrack, Magneto]
-
A.
Magneto
chosen
Magneto is a powerful Marvel Comics supervillain and occasional antihero, known as a mutant with magnetic abilities and a complex ideological rivalry with the X-Men.
-
B.
Wolverine
Wolverine is a higher-speed Amtrak passenger train service that operates multiple daily routes between Chicago, Detroit, and Pontiac in the Midwestern United States.
-
C.
Wolverine
Wolverine is a fierce, small but powerful mammal known for its strength, tenacity, and association with toughness in sports and popular culture.
-
D.
Wolverine
Wolverine is a popular Marvel Comics mutant superhero known for his retractable adamantium claws, accelerated healing factor, and membership in the X-Men.
-
E.
Mr. Sinister
Mr. Sinister is a sinister geneticist and long-time X-Men supervillain in Marvel Comics, known for his obsession with mutant experimentation and manipulation.
- 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_69d8e51e7d948190aedbcd6c30361c39 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e6586e8b648190bb650d7f2816dda1 |
completed | April 20, 2026, 4:46 p.m. |
Created at: April 10, 2026, 1:51 p.m.