Triple
T3785017
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Casper (1995 film) |
E85509
|
entity |
| Predicate | mainCharacter |
P1183
|
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: [Casper (1995 film), mainCharacter, Casper]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Casper Context triple: [Casper (1995 film), mainCharacter, 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.
Elmore
Elmore is the birth name of American actor Rip Torn, a prolific character performer known for his intense screen presence and roles in projects like "The Larry Sanders Show" and "Men in Black."
-
E.
Chico
Chico is a mid-sized city in Northern California known for California State University, Chico, and its large urban park, Bidwell Park.
- 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_69aed937fa8881908208ef3801060826 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aee3dd80f08190a1704521a764e22c |
completed | March 9, 2026, 3:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b503eca8408190ae35aeffc2dc1e6c |
completed | March 14, 2026, 6:45 a.m. |
Created at: March 9, 2026, 3:13 p.m.