Triple
T22785676
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jacinta de Jesus Marto |
E563958
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Jacinta |
—
|
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: Jacinta | Statement: [Jacinta de Jesus Marto, givenName, Jacinta]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jacinta Context triple: [Jacinta de Jesus Marto, givenName, Jacinta]
-
A.
Jacinta
chosen
Jacinta is a feminine given name of Spanish and Portuguese origin, famously borne by Jacinta Marto, one of the child visionaries of Fátima.
-
B.
Ondina
Ondina is a traditional female character featured in the Viareggio Carnival, often embodying the festive, allegorical spirit of this famous Italian celebration.
-
C.
Aleta
Aleta is a central character in the Prince Valiant saga, known as the intelligent and noble Queen of the Misty Isles and the beloved wife of the hero Prince Valiant.
-
D.
Soléa
Soléa is the public transport operator responsible for managing and running the urban bus and tram network in Mulhouse, France.
-
E.
Faina
Faina is a feminine given name, notably borne by the celebrated Soviet actress Faina Ranevskaya.
- 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_69e2455500788190b4b33030461f3bbd |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17c30b4dc8190a5e23f4ce7feb300 |
completed | April 29, 2026, 3:34 a.m. |
Created at: April 17, 2026, 3:29 p.m.