Triple
T10118313
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maria Cantwell |
E223218
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Maria |
E103006
|
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: Maria | Statement: [Maria Cantwell, givenName, Maria]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Maria Context triple: [Maria Cantwell, givenName, Maria]
-
A.
Maria
chosen
Maria is a female given name of Latin origin meaning "beloved" or "wished-for child," widely used across many cultures and languages.
-
B.
Maria
Maria is the protagonist of Paulo Coelho's novel "Eleven Minutes," a young Brazilian woman whose journey explores themes of love, sexuality, and self-discovery.
-
C.
Maria
Maria is a witty and sharp-tongued gentlewoman in Olivia’s household in Shakespeare’s comedy "Twelfth Night," known for her clever schemes and playful manipulation of other characters.
-
D.
Maria
Maria is a coastal municipality on Siquijor Island in the Philippines known for its rural communities and scenic seaside landscapes.
-
E.
Maria
Maria is a key character in the historical drama "Tulip Fever," serving as the young maid whose secret romance and pregnancy help drive the film’s central scheme and emotional stakes.
- 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_69ca8422047c81909d66b717b8b18cf3 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cdd26460a4819093a3b239d97c3e3d |
completed | April 2, 2026, 2:20 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d2cc350310819096cca4cc251e3428 |
completed | April 5, 2026, 8:55 p.m. |
Created at: March 30, 2026, 9:04 p.m.