Triple
T9235615
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Book of Eli |
E221928
|
entity |
| Predicate | character |
P662
|
FINISHED |
| Object | Carnegie |
E229
|
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: Carnegie | Statement: [The Book of Eli, character, Carnegie]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Carnegie Context triple: [The Book of Eli, character, Carnegie]
-
A.
Carnegie
chosen
Carnegie is a Scottish surname most famously associated with industrialist and philanthropist Andrew Carnegie.
-
B.
Swasey
Swasey is a surname of English origin borne by various notable individuals, including architects, politicians, and academics.
-
C.
Carnegie, Pennsylvania
Carnegie, Pennsylvania is a small borough in Allegheny County near Pittsburgh, historically tied to the region’s steel industry and local immigrant communities.
-
D.
Andrew Carnegie Free Library & Music Hall
The Andrew Carnegie Free Library & Music Hall is a historic cultural complex in Carnegie, Pennsylvania, that combines a public library with a performance venue and community event space.
-
E.
Peabody
Peabody is a suburban city in northeastern Massachusetts known for its location on the North Shore and its historical ties to the leather industry.
- 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_69ca83ed628c8190bc02d641e57f097f |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69ccf09d42488190b8ccb9c4b62fdda8 |
completed | April 1, 2026, 10:17 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d077cc774c8190bdbdd4071c11f096 |
completed | April 4, 2026, 2:30 a.m. |
Created at: March 30, 2026, 7:29 p.m.