Triple
T5172719
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vanessa |
E116721
|
entity |
| Predicate | hasVariantSpelling |
P457
|
FINISHED |
| Object | Vanesa |
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: Vanesa | Statement: [Vanessa, hasVariantSpelling, Vanesa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vanesa Context triple: [Vanessa, hasVariantSpelling, Vanesa]
-
A.
Vanessa
chosen
Vanessa is an English feminine given name that gained wider recognition through public figures such as Vanessa Trump.
-
B.
Daniela
Daniela is a feminine given name commonly used in many languages, often as the female form of Daniel.
-
C.
Vanessa Marquez
Vanessa Marquez is an American R&B singer best known for her early-2000s work with Pharrell Williams and The Neptunes, including her feature on N.E.R.D’s hit single “Frontin’.”
-
D.
Yovanna
Yovanna is a fictional character played by actress Adria Arjona, known from her work in film and television.
-
E.
Consuelo
Consuelo is a feminine given name of Spanish origin, historically associated with figures such as American socialite Consuelo Vanderbilt.
- 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_69bd445ff97c81909a2615cc56235470 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd795252a481908634779f3f656574 |
completed | March 20, 2026, 4:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bed9471b4881909c8436853818a8a0 |
completed | March 21, 2026, 5:45 p.m. |
Created at: March 20, 2026, 1:45 p.m.