Triple
T23552749
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Todd McFarlane |
E578095
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | McFarlane |
—
|
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: McFarlane | Statement: [Todd McFarlane, familyName, McFarlane]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: McFarlane Context triple: [Todd McFarlane, familyName, McFarlane]
-
A.
McFarlane
chosen
McFarlane is a Scottish surname associated with Clan MacFarlane, a historic Highland clan from the area around Loch Lomond.
-
B.
Kenner Products
Kenner Products was an American toy company best known for producing popular licensed toy lines such as the original Star Wars action figures.
-
C.
Kenner
Kenner is a suburban city in the New Orleans metropolitan area of Louisiana, known for its proximity to Louis Armstrong New Orleans International Airport and the Mississippi River.
-
D.
Kenner
Kenner is a surname most notably associated with Hugh Kenner, a prominent Canadian literary critic and scholar of modernist literature.
-
E.
Smodco
Smodco is Kevin Smith’s multimedia production company, best known for producing his films, podcasts, and related View Askewniverse projects.
- 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_69e245fa93448190919cb04534560542 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f1aed096b08190a8a755eaa7663fba |
completed | April 29, 2026, 7:10 a.m. |
Created at: April 17, 2026, 6:11 p.m.