Triple
T13350614
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brad Silberling |
E318058
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Casper |
E85509
|
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: Casper | Statement: [Brad Silberling, notableWork, Casper]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Casper Context triple: [Brad Silberling, notableWork, Casper]
-
A.
Casper
chosen
Casper is a 1995 family fantasy film about a friendly ghost who befriends a young girl while haunting a crumbling mansion.
-
B.
Casper, Wyoming
Casper, Wyoming is a city in central Wyoming known historically as an oil boomtown and regional hub for energy, commerce, and outdoor recreation.
-
C.
Casperia
Casperia is a historic hilltop village in central Italy’s Lazio region, known for its medieval architecture and panoramic views over the Sabine countryside.
-
D.
Garson
Garson is a masculine given name most notably associated with American writer and director Garson Kanin.
-
E.
Elmore
Elmore is a fictional, suburban American town characterized by its bizarre residents and surreal events in the animated series "The Amazing World of Gumball."
- 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_69d806b5a3c08190b42c267fb092f98a |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d99e8c2f1c819094f0970f35f18afa |
completed | April 11, 2026, 1:06 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f71f47fd7c8190b8d98a181acd7710 |
completed | May 3, 2026, 10:11 a.m. |
Created at: April 9, 2026, 9:31 p.m.