Triple
T8042329
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leonora Carrington |
E187468
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Leonora |
E180426
|
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: Leonora | Statement: [Leonora Carrington, givenName, Leonora]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Leonora Context triple: [Leonora Carrington, givenName, Leonora]
-
A.
Leonora
chosen
Leonora is a feminine given name used in various cultures, often considered a variant of Eleanor or Leonore.
-
B.
Leonora
Leonora is a remote mining town in Western Australia’s Goldfields-Esperance region, historically significant for its goldfields and outback heritage.
-
C.
Rosabella
Rosabella is the shy, kind-hearted waitress who becomes the central romantic heroine in Frank Loesser’s Broadway musical "The Most Happy Fella."
-
D.
Luciana
Luciana is a feminine given name of Latin origin, commonly used in Spanish- and Portuguese-speaking countries.
-
E.
Caterina
Caterina is an Italian given name, equivalent to Catherine, commonly used for women in Italian-speaking and related cultures.
- 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_69ca82b00cb48190b59a300f70e97bd7 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3f49dcfc81909ac7c93e19ad05c2 |
completed | March 31, 2026, 3:28 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cc5706a4a881909758ea34cf5c0cf2 |
completed | March 31, 2026, 11:21 p.m. |
Created at: March 30, 2026, 5:23 p.m.