Triple
T14411866
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Raymond & Ray |
E357348
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Julie Lynn |
E684635
|
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: Julie Lynn | Statement: [Raymond & Ray, producer, Julie Lynn]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Julie Lynn Context triple: [Raymond & Ray, producer, Julie Lynn]
-
A.
Julie Lynn
chosen
Julie Lynn is an American film producer known for her work on independent and critically acclaimed movies.
-
B.
Julie Leonard
Julie Leonard was the wife of American film director Norman Taurog, known for her connection to his long career in Hollywood.
-
C.
Julie Alexander
Julie Alexander is an American businesswoman and former wife of legendary television and radio host Larry King.
-
D.
Julie Alexander
Julie Alexander is a person whose specific public identity or notable achievements are not clearly defined from the given information.
-
E.
Julie Carmen
Julie Carmen is an American actress and licensed psychotherapist best known for her roles in films such as "Gloria" (1980), "Milagro Beanfield War," and various television series.
- 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_69d82793421c8190861eb0e673b085de |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de90cb3c708190822f5506ebf7ee9d |
completed | April 14, 2026, 7:08 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a018c30b5388190b5c4190d89c7ae97 |
completed | May 11, 2026, 7:58 a.m. |
Created at: April 10, 2026, 1:17 a.m.