Triple
T16109599
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kimiko Glenn |
E390838
|
entity |
| Predicate | characterPortrayed |
P1507
|
FINISHED |
| Object | Bridgette |
E214474
|
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: Bridgette | Statement: [Kimiko Glenn, characterPortrayed, Bridgette]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bridgette Context triple: [Kimiko Glenn, characterPortrayed, Bridgette]
-
A.
Bridgette
chosen
Bridgette is a feminine given name commonly used in English-speaking countries, often considered a variant of "Bridget."
-
B.
Bridget
Bridget is a feminine given name most notably associated with American actress Bridget Fonda.
-
C.
Bridget
Bridget is a fictional character portrayed by American actress Elinor Donahue, known for her work in classic film and television.
-
D.
Adrienne
Adrienne is a feminine given name of French origin, commonly used in English- and French-speaking countries.
-
E.
Tiffani
Tiffani is a given name, typically a modern variant of the name Tiffany used for girls.
- 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_69d87f1a8dd881909f1de6ef78849874 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e2016665c0819081aa7a44b1d08183 |
completed | April 17, 2026, 9:46 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fff2a16acc8190be9ed181c7a44def |
completed | May 10, 2026, 2:51 a.m. |
Created at: April 10, 2026, 5 a.m.