Triple
T11121286
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kevin McGibbon |
E263021
|
entity |
| Predicate | hasRelative |
P367
|
FINISHED |
| Object |
Ted McGibbon
Ted McGibbon is an individual known primarily as a relative of Kevin McGibbon.
|
E931660
|
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: Ted McGibbon | Statement: [Kevin McGibbon, hasRelative, Ted McGibbon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ted McGibbon Context triple: [Kevin McGibbon, hasRelative, Ted McGibbon]
-
A.
Ted McGibbon
Ted McGibbon is a fictional character portrayed by actor Larry Anderson, likely appearing in a television series or film.
-
B.
Ed McHugh
Ed McHugh is a relative of American character actor Frank McHugh, who was known for his prolific work in early 20th-century film and theater.
-
C.
Ed McCauley
Ed McCauley is a Canadian academic and research leader who serves as president of the University of Calgary.
-
D.
Bill McGowan
Bill McGowan was a prominent American Major League Baseball umpire renowned for his long career, authoritative style, and induction into the Baseball Hall of Fame.
-
E.
Ray McKinnon
Ray McKinnon is an American actor, writer, producer, and director known for his character roles in film and television and for creating the acclaimed series "Rectify."
- 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: Ted McGibbon Triple: [Kevin McGibbon, hasRelative, Ted McGibbon]
Generated description
Ted McGibbon is an individual known primarily as a relative of Kevin McGibbon.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ted McGibbon Target entity description: Ted McGibbon is an individual known primarily as a relative of Kevin McGibbon.
-
A.
Ted McGibbon
Ted McGibbon is a fictional character portrayed by actor Larry Anderson, likely appearing in a television series or film.
-
B.
Ed McHugh
Ed McHugh is a relative of American character actor Frank McHugh, who was known for his prolific work in early 20th-century film and theater.
-
C.
Ed McCauley
Ed McCauley is a Canadian academic and research leader who serves as president of the University of Calgary.
-
D.
Bill McGowan
Bill McGowan was a prominent American Major League Baseball umpire renowned for his long career, authoritative style, and induction into the Baseball Hall of Fame.
-
E.
Ray McKinnon
Ray McKinnon is an American actor, writer, producer, and director known for his character roles in film and television and for creating the acclaimed series "Rectify."
- 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_69d6aa9b46cc8190b19f9f0cc45bf322 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d79af911b881908168f23a4918231c |
completed | April 9, 2026, 12:26 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e6849dbff08190a352eaaea8606bdb |
completed | April 20, 2026, 7:55 p.m. |
| NEDg | Description generation | batch_69e68ce8d7988190a0dd3abe5f2afc97 |
completed | April 20, 2026, 8:30 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69e6b7a31b4081909b06bc9b6d0a1617 |
completed | April 20, 2026, 11:32 p.m. |
Created at: April 8, 2026, 9:28 p.m.