Triple
T18425317
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mary Josephine Hannon Fitzgerald |
E442122
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Hannon |
—
|
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: Hannon | Statement: [Mary Josephine Hannon Fitzgerald, familyName, Hannon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hannon Context triple: [Mary Josephine Hannon Fitzgerald, familyName, Hannon]
-
A.
Hannon
chosen
Hannon is an Irish surname historically associated with families of Irish origin, including that of Mary Josephine Hannon Fitzgerald, mother of Rose Kennedy.
-
B.
Hindmarch
Hindmarch is an English surname most notably associated with British fashion designer Anya Hindmarch.
-
C.
Hackett
Hackett is the middle name of David H. Souter, a former Associate Justice of the United States Supreme Court.
-
D.
Hackett
Hackett is a surname of English and Irish origin borne by various notable individuals across fields such as literature, sports, and entertainment.
-
E.
Hannen
Hannen is an English surname associated with several notable figures, including actors and judges, in British history.
- 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_69d8b9eb8a508190a942fd75ebd8b1dc |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e51b12606081908ea320fd8d5554c6 |
completed | April 19, 2026, 6:12 p.m. |
Created at: April 10, 2026, 10:47 a.m.