Triple
T1870522
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mary Ann Holmes Booth |
E39024
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Mary Ann |
E96798
|
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: Mary Ann | Statement: [Mary Ann Holmes Booth, givenName, Mary Ann]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mary Ann Context triple: [Mary Ann Holmes Booth, givenName, Mary Ann]
-
A.
Mary Ann
chosen
Mary Ann is the namesake of the city of Marianna in Florida.
-
B.
Betsy
Betsy is a key female character in the 1976 film "Taxi Driver," known as the idealistic campaign worker who becomes the object of Travis Bickle’s fixation.
-
C.
Adria Fanny Heath
Adria Fanny Heath was the mother of Lord Chelmsford, a British peer and colonial administrator.
-
D.
Abigail
Abigail is a feminine given name of Hebrew origin meaning "my father is joy," historically popular in English-speaking countries.
-
E.
Henrietta
Henrietta is a feminine given name of English origin, historically popular in the 18th and 19th centuries and borne by several notable figures.
- 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_69a8862f7074819096afe7fe65e179e9 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb0b95c0c8190a37907755541f8c6 |
completed | March 7, 2026, 4:59 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69add1dab2a481909adb0a3132348cee |
completed | March 8, 2026, 7:45 p.m. |
Created at: March 4, 2026, 7:34 p.m.