Triple
T4173340
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Margaret Cuomo |
E86414
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Margaret |
E17722
|
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: Margaret | Statement: [Margaret Cuomo, givenName, Margaret]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Margaret Context triple: [Margaret Cuomo, givenName, Margaret]
-
A.
Margaret
chosen
Margaret is a feminine given name of Greek origin, traditionally associated with the meaning "pearl" and widely used in English-speaking countries.
-
B.
Margaret
Margaret is a 2011 American drama film written and directed by Kenneth Lonergan, known for its complex portrayal of grief and moral responsibility following a tragic bus accident in New York City.
-
C.
Margaret Mara
Margaret Mara is a person notable enough to be recognized as a bearer of the surname Mara, though specific widely known public details about her are not clearly established.
-
D.
Margaret Rose
Margaret Rose, better known as Princess Margaret, was the younger sister of Queen Elizabeth II and a prominent British royal noted for her glamorous yet often controversial life.
-
E.
Marjorie
Marjorie is a feminine given name of French origin that has been widely used in English-speaking countries.
- 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_69aed93de98c8190ad838ce507b77c8a |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af02e65b548190be095df62091b960 |
completed | March 9, 2026, 5:27 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b57f5428a0819082aaea8950a7c039 |
completed | March 14, 2026, 3:31 p.m. |
Created at: March 9, 2026, 3:45 p.m.