Triple
T7242392
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Frank McCourt |
E156386
|
entity |
| Predicate | hasChild |
P369
|
FINISHED |
| Object |
Morgan McCourt
Morgan McCourt is one of the children of Pulitzer Prize–winning Irish-American author Frank McCourt.
|
E654434
|
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: Morgan McCourt | Statement: [Frank McCourt, hasChild, Morgan McCourt]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Morgan McCourt Context triple: [Frank McCourt, hasChild, Morgan McCourt]
-
A.
Megan Walsh
Megan Walsh is the teenage government-trained assassin who goes undercover as a high school student in the action-comedy film "Barely Lethal."
-
B.
Molly McCauley
Molly McCauley, better known as Molly Pitcher, is a legendary figure of the American Revolutionary War celebrated for taking her husband's place at a cannon during the Battle of Monmouth.
-
C.
Rebecca McGuinness
Rebecca McGuinness is known as the wife of renowned English motorcycle road racer John McGuinness.
-
D.
Meghan McDermott
Meghan McDermott is an American public relations and communications professional best known for her marriage to actor Theo Rossi.
-
E.
Morgan Alexander
Morgan Alexander is a fictional character in the romantic sports film "Just Wright," which centers on basketball and personal relationships.
- 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: Morgan McCourt Triple: [Frank McCourt, hasChild, Morgan McCourt]
Generated description
Morgan McCourt is one of the children of Pulitzer Prize–winning Irish-American author Frank McCourt.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Morgan McCourt Target entity description: Morgan McCourt is one of the children of Pulitzer Prize–winning Irish-American author Frank McCourt.
-
A.
Megan Walsh
Megan Walsh is the teenage government-trained assassin who goes undercover as a high school student in the action-comedy film "Barely Lethal."
-
B.
Molly McCauley
Molly McCauley, better known as Molly Pitcher, is a legendary figure of the American Revolutionary War celebrated for taking her husband's place at a cannon during the Battle of Monmouth.
-
C.
Rebecca McGuinness
Rebecca McGuinness is known as the wife of renowned English motorcycle road racer John McGuinness.
-
D.
Meghan McDermott
Meghan McDermott is an American public relations and communications professional best known for her marriage to actor Theo Rossi.
-
E.
Morgan Alexander
Morgan Alexander is a fictional character in the romantic sports film "Just Wright," which centers on basketball and personal relationships.
- 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_69c68827b5e481908dc05e145b2c92d4 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6ea56756c8190996c2390902f166a |
completed | March 27, 2026, 8:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7db0fd90881908c6b84f1292f0b01 |
completed | March 28, 2026, 1:43 p.m. |
| NEDg | Description generation | batch_69c7df2bb57c81909f08b565fe739166 |
completed | March 28, 2026, 2:01 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c7df7c65e481908eb5c92168429d5a |
completed | March 28, 2026, 2:02 p.m. |
Created at: March 27, 2026, 2:55 p.m.