Triple
T3239425
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Murphy |
E67931
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object |
Jim Murphy
Jim Murphy is a Scottish Labour Party politician who served as a Member of Parliament and held several senior roles in the UK government and his party.
|
E341013
|
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: Jim Murphy | Statement: [Murphy, hasNotableBearer, Jim Murphy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jim Murphy Context triple: [Murphy, hasNotableBearer, Jim Murphy]
-
A.
Ed Gainey
Ed Gainey is an American politician who became the first Black mayor of Pittsburgh, Pennsylvania.
-
B.
Mike Dunleavy
Mike Dunleavy is an American Republican politician and former educator who serves as the governor of Alaska.
-
C.
Pat Quinn
Pat Quinn was a highly respected Canadian NHL coach and executive known for leading multiple teams to deep playoff runs and coaching Team Canada to international success.
-
D.
Mike Sullivan
Mike Sullivan is an American professional ice hockey coach best known for leading the Pittsburgh Penguins to multiple Stanley Cup championships.
-
E.
Michael Hogan
Michael Hogan was a screenwriter known for his work on classic Hollywood films, including contributing to the script of Alfred Hitchcock’s 1940 adaptation of "Rebecca."
- 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: Jim Murphy Triple: [Murphy, hasNotableBearer, Jim Murphy]
Generated description
Jim Murphy is a Scottish Labour Party politician who served as a Member of Parliament and held several senior roles in the UK government and his party.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Jim Murphy Target entity description: Jim Murphy is a Scottish Labour Party politician who served as a Member of Parliament and held several senior roles in the UK government and his party.
-
A.
Ed Gainey
Ed Gainey is an American politician who became the first Black mayor of Pittsburgh, Pennsylvania.
-
B.
Mike Dunleavy
Mike Dunleavy is an American Republican politician and former educator who serves as the governor of Alaska.
-
C.
Pat Quinn
Pat Quinn was a highly respected Canadian NHL coach and executive known for leading multiple teams to deep playoff runs and coaching Team Canada to international success.
-
D.
Mike Sullivan
Mike Sullivan is an American professional ice hockey coach best known for leading the Pittsburgh Penguins to multiple Stanley Cup championships.
-
E.
Michael Hogan
Michael Hogan was a screenwriter known for his work on classic Hollywood films, including contributing to the script of Alfred Hitchcock’s 1940 adaptation of "Rebecca."
- 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_69ad858d27348190abb61c280b4c86a9 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69adaef4c0bc819095e4f84296fe7cb6 |
completed | March 8, 2026, 5:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b2774f93448190b8493b457636ae48 |
completed | March 12, 2026, 8:20 a.m. |
| NEDg | Description generation | batch_69b2786b7d388190ad0d97bd41a60543 |
completed | March 12, 2026, 8:25 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b27c45f6b08190966fbc3fd28664ec |
completed | March 12, 2026, 8:41 a.m. |
Created at: March 8, 2026, 3:08 p.m.