Triple
T5182667
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Úrsula Corberó |
E116957
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Úrsula |
E313707
|
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: Úrsula | Statement: [Úrsula Corberó, givenName, Úrsula]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Úrsula Context triple: [Úrsula Corberó, givenName, Úrsula]
-
A.
Ursula
Ursula is the iconic sea witch villain from Disney's animated film "The Little Mermaid," known for her dark magic, cunning bargains, and memorable musical number "Poor Unfortunate Souls."
-
B.
Ursula
chosen
Ursula is a feminine given name of Latin origin, most famously borne by Ursula von der Leyen, the President of the European Commission.
-
C.
Rosalinda
Rosalinda is a feminine given name of Spanish and Italian origin, often interpreted to mean "beautiful rose."
-
D.
Clorinda
Clorinda is a border city in northeastern Argentina’s Formosa Province, located opposite Asunción, Paraguay, and serving as an important regional commercial and transport hub.
-
E.
Santa Úrsula
Santa Úrsula is a neighborhood in Mexico City best known for hosting the iconic Estadio Azteca football stadium.
- 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_69bd446140f08190becb93c61158f27f |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd799d50388190bf2b7dfdd90949e9 |
completed | March 20, 2026, 4:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bed95b2900819082b534e27484171e |
completed | March 21, 2026, 5:46 p.m. |
Created at: March 20, 2026, 1:46 p.m.