Triple
T12905657
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | An Innocent Man |
E308722
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Christie Lee |
E1010455
|
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: Christie Lee | Statement: [An Innocent Man, hasPart, Christie Lee]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Christie Lee Context triple: [An Innocent Man, hasPart, Christie Lee]
-
A.
Christie Lee
chosen
"Christie Lee" is a song by Billy Joel from his 1983 album "An Innocent Man," known for its rock and roll style and narrative lyrics.
-
B.
Christine Lee
Christine Lee is an actress best known for her role in the Netflix zombie apocalypse series "Black Summer."
-
C.
Claudia Lee
Claudia Lee is an American actress and singer best known for her role as Magnolia Breeland on the television series "Hart of Dixie."
-
D.
Connie Chung
Connie Chung is an American broadcast journalist and television news anchor known for her work on major U.S. networks and high-profile interviews.
-
E.
Linda Cho
Linda Cho is a Tony Award–winning costume designer known for her work on major Broadway productions and other theatrical performances.
- 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_69d7bdf92b588190acdf2a2291ac4590 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d971831bd48190b0ecd13e7181bbc6 |
completed | April 10, 2026, 9:54 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6b8cec96c819089d253162bc4705a |
completed | May 3, 2026, 2:54 a.m. |
Created at: April 9, 2026, 5:41 p.m.