Triple
T3624123
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Candice Bergen |
E76795
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Candice |
E247927
|
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: Candice | Statement: [Candice Bergen, givenName, Candice]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Candice Context triple: [Candice Bergen, givenName, Candice]
-
A.
Candice
chosen
Candice is a feminine given name commonly used in English-speaking countries, often associated with the meaning "clarity" or "purity."
-
B.
Candace
Candace is a central female character in the romantic comedy film "Think Like a Man," portrayed as a single mother navigating love and relationships while inspired by Steve Harvey’s dating advice.
-
C.
Danielle
"Danielle" is a work created by Sarah Churchill, known as part of her contributions to the arts.
-
D.
Nicole
Nicole is a central character in Margaret Atwood's dystopian novel "The Testaments," whose story helps expose and challenge the oppressive regime of Gilead.
-
E.
Adrienne
Adrienne is a feminine given name of French origin, commonly used in English- and French-speaking countries.
- 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_69ad85dc03948190b35b7189e4175bcc |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc2d9845c8190ad65b2471000dfa0 |
completed | March 8, 2026, 6:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4332260cc8190964a15bfee0a3b61 |
completed | March 13, 2026, 3:54 p.m. |
Created at: March 8, 2026, 3:23 p.m.