Triple
T3374364
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Juliette Lewis |
E71030
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Juliette |
E265942
|
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: Juliette | Statement: [Juliette Lewis, givenName, Juliette]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Juliette Context triple: [Juliette Lewis, givenName, Juliette]
-
A.
Juliette
chosen
Juliette is a feminine given name of French origin, widely used in many countries and popularized through literature and film.
-
B.
Laetitia
Laetitia is a feminine given name of Latin origin, historically borne by figures such as the English poet and essayist Anna Laetitia Barbauld.
-
C.
Jeanne
Jeanne was a common French female given name historically borne by notable figures such as queens, saints, and writers.
-
D.
Renée
Renée is a feminine given name of French origin, commonly used in French-speaking countries and beyond.
-
E.
Pierrette
Pierrette is a French feminine given name, traditionally considered the female form of Pierre.
- 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_69ad85a7f80c8190a05e43013f298942 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb2bf4ad88190a2c49dc30f323a13 |
completed | March 8, 2026, 5:32 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b33442f28c8190b48a662a5dd1bac3 |
completed | March 12, 2026, 9:46 p.m. |
Created at: March 8, 2026, 3:13 p.m.