Triple
T9385854
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paper Girls (TV series) |
E225901
|
entity |
| Predicate | mainCharacter |
P1183
|
FINISHED |
| Object |
Mac Coyle
Mac Coyle is a tough, sharp-tongued 12-year-old paper delivery girl from the 1980s who becomes embroiled in a time-traveling adventure in the sci-fi series "Paper Girls."
|
E804724
|
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: Mac Coyle | Statement: [Paper Girls (TV series), mainCharacter, Mac Coyle]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mac Coyle Context triple: [Paper Girls (TV series), mainCharacter, Mac Coyle]
-
A.
Mike O’Shea
Mike O’Shea is a Canadian football coach and former linebacker best known for leading the Winnipeg Blue Bombers to multiple Grey Cup championships in the CFL.
-
B.
Jeff Cooney
Jeff Cooney is a television producer best known for his executive production work on the biographical anthology series "Genius."
-
C.
Kevin O'Connell
Kevin O'Connell is an American football coach and former NFL quarterback who serves as the head coach of the Minnesota Vikings.
-
D.
Jim Cahill
Jim Cahill is a person notable enough to be recognized as a prominent bearer of the Cahill surname.
-
E.
Ed McCauley
Ed McCauley is a Canadian academic and research leader who serves as president of the University of Calgary.
- 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: Mac Coyle Triple: [Paper Girls (TV series), mainCharacter, Mac Coyle]
Generated description
Mac Coyle is a tough, sharp-tongued 12-year-old paper delivery girl from the 1980s who becomes embroiled in a time-traveling adventure in the sci-fi series "Paper Girls."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mac Coyle Target entity description: Mac Coyle is a tough, sharp-tongued 12-year-old paper delivery girl from the 1980s who becomes embroiled in a time-traveling adventure in the sci-fi series "Paper Girls."
-
A.
Mike O’Shea
Mike O’Shea is a Canadian football coach and former linebacker best known for leading the Winnipeg Blue Bombers to multiple Grey Cup championships in the CFL.
-
B.
Jeff Cooney
Jeff Cooney is a television producer best known for his executive production work on the biographical anthology series "Genius."
-
C.
Kevin O'Connell
Kevin O'Connell is an American football coach and former NFL quarterback who serves as the head coach of the Minnesota Vikings.
-
D.
Jim Cahill
Jim Cahill is a person notable enough to be recognized as a prominent bearer of the Cahill surname.
-
E.
Ed McCauley
Ed McCauley is a Canadian academic and research leader who serves as president of the University of Calgary.
- 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_69ca842e9dcc8190a264119e683cfe04 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd50d3964c8190b0353f56df755db8 |
completed | April 1, 2026, 5:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d14bdb000c81909b11b3bf2398bf0f |
completed | April 4, 2026, 5:35 p.m. |
| NEDg | Description generation | batch_69d14cbfcbbc8190b6601a99dc773cb3 |
completed | April 4, 2026, 5:39 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d14d29d32c8190a8615b3450492abc |
completed | April 4, 2026, 5:40 p.m. |
Created at: March 30, 2026, 7:44 p.m.