Triple
T10721901
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John McGiver |
E252841
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object |
Mr. Novak
Mr. Novak is an American television drama series from the 1960s centered on a compassionate high school English teacher navigating educational and social issues.
|
E882162
|
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: Mr. Novak | Statement: [John McGiver, notableWork, Mr. Novak]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mr. Novak Context triple: [John McGiver, notableWork, Mr. Novak]
-
A.
Mr. Franks
Mr. Franks is a music producer best known for his work with the hip-hop collective Legend.
-
B.
John Norville
John Norville is a screenwriter best known for co-writing the story for Disney's adventure film "Jungle Cruise."
-
C.
William Novak
William Novak is an American writer and ghostwriter best known for co-authoring high-profile political and celebrity memoirs.
-
D.
Marvin Krislov
Marvin Krislov is an American academic leader and former president of Oberlin College who serves as the president of Pace University in New York.
-
E.
Stanley Mazor
Stanley Mazor is an American computer engineer best known as one of the key designers of the first commercial microprocessor and an early pioneer in microprocessor architecture at Intel.
- 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: Mr. Novak Triple: [John McGiver, notableWork, Mr. Novak]
Generated description
Mr. Novak is an American television drama series from the 1960s centered on a compassionate high school English teacher navigating educational and social issues.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mr. Novak Target entity description: Mr. Novak is an American television drama series from the 1960s centered on a compassionate high school English teacher navigating educational and social issues.
-
A.
Mr. Franks
Mr. Franks is a music producer best known for his work with the hip-hop collective Legend.
-
B.
John Norville
John Norville is a screenwriter best known for co-writing the story for Disney's adventure film "Jungle Cruise."
-
C.
William Novak
William Novak is an American writer and ghostwriter best known for co-authoring high-profile political and celebrity memoirs.
-
D.
Marvin Krislov
Marvin Krislov is an American academic leader and former president of Oberlin College who serves as the president of Pace University in New York.
-
E.
Stanley Mazor
Stanley Mazor is an American computer engineer best known as one of the key designers of the first commercial microprocessor and an early pioneer in microprocessor architecture at Intel.
- 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_69d6aa5d8be481909a43218b2bfdbe95 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d70d43655081909b071100c96cb4f6 |
completed | April 9, 2026, 2:21 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69dbb738f8488190837a675b82ce75aa |
completed | April 12, 2026, 3:16 p.m. |
| NEDg | Description generation | batch_69dbbbe545748190b2bdbc3a75224eb0 |
completed | April 12, 2026, 3:36 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69dbc59b315081909362892f5b989d25 |
completed | April 12, 2026, 4:17 p.m. |
Created at: April 8, 2026, 9:13 p.m.