Triple
T2692926
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Durkan |
E58445
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object |
Mary Durkan
Mary Durkan is an Irish politician known for her involvement in local and national public affairs.
|
E303876
|
NE FINISHED |
How this triple was built (4 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 Durkan | Statement: [Durkan, hasNotableBearer, Mary Durkan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mary Durkan Context triple: [Durkan, hasNotableBearer, Mary Durkan]
-
A.
Mary Mulhern
Mary Mulhern was an American actress best known for her brief Hollywood career in the silent film era and her marriage to actor Jack Pickford.
-
B.
Helen O’Connell
Helen O’Connell was a popular American big band singer and entertainer best known for her work with Jimmy Dorsey’s orchestra in the 1940s.
-
C.
Eileen Guinness
Eileen Guinness was the wife of pioneering statistician and geneticist Ronald A. Fisher, connected to him during his influential career in early 20th-century science.
-
D.
Yvonne McGuinness
Yvonne McGuinness is an Irish visual artist and filmmaker known for her multimedia installations and video art.
-
E.
Orla Fitzgerald
Orla Fitzgerald is an Irish actress best known for her role in the historical drama film "The Wind That Shakes the Barley."
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Mary Durkan Triple: [Durkan, hasNotableBearer, Mary Durkan]
Generated description
Mary Durkan is an Irish politician known for her involvement in local and national public affairs.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mary Durkan Target entity description: Mary Durkan is an Irish politician known for her involvement in local and national public affairs.
-
A.
Mary Mulhern
Mary Mulhern was an American actress best known for her brief Hollywood career in the silent film era and her marriage to actor Jack Pickford.
-
B.
Helen O’Connell
Helen O’Connell was a popular American big band singer and entertainer best known for her work with Jimmy Dorsey’s orchestra in the 1940s.
-
C.
Eileen Guinness
Eileen Guinness was the wife of pioneering statistician and geneticist Ronald A. Fisher, connected to him during his influential career in early 20th-century science.
-
D.
Yvonne McGuinness
Yvonne McGuinness is an Irish visual artist and filmmaker known for her multimedia installations and video art.
-
E.
Orla Fitzgerald
Orla Fitzgerald is an Irish actress best known for her role in the historical drama film "The Wind That Shakes the Barley."
- F. None of above. chosen
Provenance (5 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_69ab4ac269e481909cb317d79e68b75b |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abda0dd97c81909a60cf200f57c087 |
completed | March 7, 2026, 7:55 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afe8920e64819099074f019020bb59 |
completed | March 10, 2026, 9:46 a.m. |
| NEDg | Description generation | batch_69afe92b8c4c8190a91c1e8564f412ad |
completed | March 10, 2026, 9:49 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b008cbabc4819090cc20cf990d16e6 |
completed | March 10, 2026, 12:04 p.m. |
Created at: March 6, 2026, 9:54 p.m.