Triple
T15982463
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alpha House |
E387607
|
entity |
| Predicate | hasCastMember |
P2308
|
FINISHED |
| Object | Julie White |
E644424
|
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 White | Statement: [Alpha House, hasCastMember, Julie White]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Julie White Context triple: [Alpha House, hasCastMember, Julie White]
-
A.
Julie White
chosen
Julie White is an American actress known for her work in film, television, and theater, including a Tony Award-winning stage career and roles in popular movies and TV series.
-
B.
Julianne White
Julianne White is an actress known for her role in the acclaimed British crime film "Sexy Beast."
-
C.
Julie Rogers
Julie Rogers is a film editor known for her work on the animated sequel "Cinderella II: Dreams Come True."
-
D.
Jill Eikenberry
Jill Eikenberry is an American actress best known for her Emmy-nominated role as attorney Ann Kelsey on the television series "L.A. Law."
-
E.
Deborah Rush
Deborah Rush is an American actress known for her character roles in film, television, and theater, including appearances in comedies and independent productions.
- 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_69d86da94ccc819083d187f5dc6a123e |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e15755b5548190acfa29eecb11e675 |
completed | April 16, 2026, 9:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a002d982788819082fcdd8ab5c80513 |
completed | May 10, 2026, 7:02 a.m. |
Created at: April 10, 2026, 4:54 a.m.