Triple
T17714976
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pam & Tommy |
E442171
|
entity |
| Predicate | executiveProducer |
P7225
|
FINISHED |
| Object |
Chip Vucelich
Chip Vucelich is a television producer best known for his executive production work on the biographical drama miniseries "Pam & Tommy."
|
E1302474
|
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: Chip Vucelich | Statement: [Pam & Tommy, executiveProducer, Chip Vucelich]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chip Vucelich Context triple: [Pam & Tommy, executiveProducer, Chip Vucelich]
-
A.
Vince Chiappetta
Vince Chiappetta is an American running advocate and organizer best known as a co-founder of the New York City Marathon.
-
B.
Vince Di Meglio
Vince Di Meglio is an American screenwriter best known for co-writing the romantic comedy film "License to Wed."
-
C.
Steve Pellegrini
Steve Pellegrini is a Canadian municipal politician who serves as the long-time mayor of the Township of King in Ontario.
-
D.
Tony Meola
Tony Meola is a former American soccer goalkeeper best known for starring with the U.S. national team in the 1990 and 1994 World Cups and for his standout career in Major League Soccer.
-
E.
Sam Pirozzolo
Sam Pirozzolo is a New York State Assembly member and Republican politician representing parts of Staten Island.
- 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: Chip Vucelich Triple: [Pam & Tommy, executiveProducer, Chip Vucelich]
Generated description
Chip Vucelich is a television producer best known for his executive production work on the biographical drama miniseries "Pam & Tommy."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Chip Vucelich Target entity description: Chip Vucelich is a television producer best known for his executive production work on the biographical drama miniseries "Pam & Tommy."
-
A.
Vince Chiappetta
Vince Chiappetta is an American running advocate and organizer best known as a co-founder of the New York City Marathon.
-
B.
Vince Di Meglio
Vince Di Meglio is an American screenwriter best known for co-writing the romantic comedy film "License to Wed."
-
C.
Steve Pellegrini
Steve Pellegrini is a Canadian municipal politician who serves as the long-time mayor of the Township of King in Ontario.
-
D.
Tony Meola
Tony Meola is a former American soccer goalkeeper best known for starring with the U.S. national team in the 1990 and 1994 World Cups and for his standout career in Major League Soccer.
-
E.
Sam Pirozzolo
Sam Pirozzolo is a New York State Assembly member and Republican politician representing parts of Staten Island.
- 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_69d8b9ec79688190b86bdcef85a7b3aa |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e4747f217081909010f396caaf03be |
completed | April 19, 2026, 6:21 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a034998e08081909bb8b9711002486f |
completed | May 12, 2026, 3:39 p.m. |
| NEDg | Description generation | batch_6a034b0817408190817e4a3ee0003d57 |
completed | May 12, 2026, 3:45 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a034bdf5c808190ac329e663e220f1b |
completed | May 12, 2026, 3:48 p.m. |
Created at: April 10, 2026, 10:06 a.m.