Triple
T20142171
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ursula Yale |
E491201
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Ursula |
—
|
NE NERFINISHED |
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: Ursula | Statement: [Ursula Yale, givenName, Ursula]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ursula Context triple: [Ursula Yale, givenName, Ursula]
-
A.
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.
-
B.
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."
-
C.
Ursula Callistis
Ursula Callistis is a fictional character, likely from a narrative work such as an anime, manga, or light novel series.
-
D.
Ariel
Ariel is the adventurous, red-haired mermaid princess from Disney’s The Little Mermaid, known for her curiosity about the human world and iconic songs like “Part of Your World.”
-
E.
Ariel
Ariel is a large Israeli settlement city in the central West Bank, known for its significant population, industrial zone, and the presence of Ariel University.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69da6265f8f0819080b29c752a574088 |
completed | April 11, 2026, 3:01 p.m. |
| NER | Named-entity recognition | batch_69e6679bcf2c8190ac6e969178d8acde |
completed | April 20, 2026, 5:51 p.m. |
Created at: April 11, 2026, 11:33 p.m.