Triple
T6189380
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vanessa Redgrave |
E138147
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Vanessa |
E116721
|
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: Vanessa | Statement: [Vanessa Redgrave, givenName, Vanessa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vanessa Context triple: [Vanessa Redgrave, givenName, Vanessa]
-
A.
Vanessa
chosen
Vanessa is an English feminine given name that gained wider recognition through public figures such as Vanessa Trump.
-
B.
Vanessa Roth
Vanessa Roth is an Academy Award-winning American documentary filmmaker known for her socially conscious films and work in education and social justice.
-
C.
Vanessa Zima
Vanessa Zima is an American actress known for her roles in films such as "Ulee's Gold" and "The Brain."
-
D.
Nicole
Nicole is a feminine given name of Greek origin meaning "victory of the people," commonly used in many English- and French-speaking countries.
-
E.
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.
- 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_69c008a8fd408190b7ec6e42934974a6 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c062192c5481909eb41f8c5d1208a3 |
completed | March 22, 2026, 9:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c16f06c770819087e055cfe6c8b134 |
completed | March 23, 2026, 4:49 p.m. |
Created at: March 22, 2026, 4:19 p.m.