Triple
T13180463
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ursula |
E313707
|
entity |
| Predicate | isUsedBy |
P1480
|
FINISHED |
| Object | Ursula Andress |
E113885
|
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: Ursula Andress | Statement: [Ursula, isUsedBy, Ursula Andress]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ursula Andress Context triple: [Ursula, isUsedBy, Ursula Andress]
-
A.
Ursula Andress
chosen
Ursula Andress is a Swiss actress best known as the iconic first Bond girl, Honey Ryder, in the James Bond film "Dr. No."
-
B.
Jill St. John
Jill St. John is an American actress best known for playing Bond girl Tiffany Case in the James Bond film "Diamonds Are Forever."
-
C.
Julie Adams
Julie Adams was an American actress best known for her role in the classic horror film "Creature from the Black Lagoon."
-
D.
Raquel Welch
Raquel Welch was an American actress and 1960s sex symbol known for her roles in adventure and fantasy films, which made her an international pop culture icon.
-
E.
Anita Ekberg
Anita Ekberg was a Swedish actress and former model best known for her iconic role in Federico Fellini’s film "La Dolce Vita."
- 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_69d806ae1e08819090d95bfe1538cc17 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98c490ed081908ea54edb25c3de90 |
completed | April 10, 2026, 11:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6ff116f1c819097e4c53cd1411d78 |
completed | May 3, 2026, 7:53 a.m. |
Created at: April 9, 2026, 9:14 p.m.