Triple
T16585517
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Julie Benz |
E402946
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Julie |
E124624
|
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 | Statement: [Julie Benz, givenName, Julie]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Julie Context triple: [Julie Benz, givenName, Julie]
-
A.
Julie
chosen
Julie is a feminine given name of Latin origin, commonly used in many Western countries.
-
B.
Julie Is Her Name
"Julie Is Her Name" is a 1955 debut studio album by jazz and pop singer Julie London, renowned for its intimate vocal style and minimalist guitar-and-bass accompaniment.
-
C.
Janet
Janet is a feminine given name commonly used in English-speaking countries, often associated with notable figures in entertainment and public life.
-
D.
Marnie
Marnie is the given name of Darcey Bussell, the renowned British ballerina and former principal dancer of The Royal Ballet.
-
E.
Marnie
Marnie is a 1964 psychological thriller film directed by Alfred Hitchcock, starring Tippi Hedren and Sean Connery, about a troubled woman with a mysterious past and compulsive thieving.
- 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_69d88387363c8190a97a0c942130de97 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3599b057881909fcb8bbb156633a8 |
completed | April 18, 2026, 10:14 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a006ef4f17c819095b3c6f8644b687b |
completed | May 10, 2026, 11:41 a.m. |
Created at: April 10, 2026, 5:16 a.m.