Triple
T21964604
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maria Ward Kirkpatrick Custer |
E542424
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Maria |
—
|
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: Maria | Statement: [Maria Ward Kirkpatrick Custer, givenName, Maria]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Maria Context triple: [Maria Ward Kirkpatrick Custer, givenName, Maria]
-
A.
Maria
Maria is an Italian woman best known as the younger sister of actress Sophia Loren and the former wife of film producer Romano Mussolini.
-
B.
Maria
chosen
Maria is a feminine given name of Hebrew origin, widely used across many cultures and languages.
-
C.
Maria
Maria is a character in the period drama film "Stage Beauty," which explores gender roles and the world of 17th-century English theatre.
-
D.
Maria
Maria is a witty and sharp-tongued lady-in-waiting to the Princess of France in William Shakespeare’s comedy "Love's Labour's Lost."
-
E.
Maria
Maria Vladimirovna Dolgorukova was a Russian noblewoman from the prominent Dolgorukov family, known historically as the first wife of Tsar Michael I of Russia.
- 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_69e0c47fab1081908dc74a6545dbb051 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f12459e1848190aa8d4ccc97f434b8 |
completed | April 28, 2026, 9:19 p.m. |
Created at: April 16, 2026, 8:01 p.m.