Triple
T15982172
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Affton, Missouri |
E387601
|
entity |
| Predicate | hasNotableResident |
P1092
|
FINISHED |
| Object |
Phil Gubala
Phil Gubala is a notable resident associated with the community of Affton, Missouri.
|
E1244729
|
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: Phil Gubala | Statement: [Affton, Missouri, hasNotableResident, Phil Gubala]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Phil Gubala Context triple: [Affton, Missouri, hasNotableResident, Phil Gubala]
-
A.
Ian Megibben
Ian Megibben is a cinematographer best known for his work on the animated film "Finding Dory."
-
B.
Ian Megibben
Ian Megibben is a cinematographer best known for his work on the animated feature film "Lightyear."
-
C.
Don Munday
Don Munday was a Canadian mountaineer and explorer renowned for his pioneering climbs and exploration of the Coast Mountains of British Columbia.
-
D.
Phil DeGuere
Phil DeGuere was an American television producer, writer, and director best known for his work on series such as Simon & Simon and the 1980s revival of The Twilight Zone.
-
E.
Greg Glienna
Greg Glienna is an American filmmaker, screenwriter, and actor best known for creating the original characters and story that inspired the "Meet the Parents" film series.
- 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: Phil Gubala Triple: [Affton, Missouri, hasNotableResident, Phil Gubala]
Generated description
Phil Gubala is a notable resident associated with the community of Affton, Missouri.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Phil Gubala Target entity description: Phil Gubala is a notable resident associated with the community of Affton, Missouri.
-
A.
Ian Megibben
Ian Megibben is a cinematographer best known for his work on the animated film "Finding Dory."
-
B.
Ian Megibben
Ian Megibben is a cinematographer best known for his work on the animated feature film "Lightyear."
-
C.
Don Munday
Don Munday was a Canadian mountaineer and explorer renowned for his pioneering climbs and exploration of the Coast Mountains of British Columbia.
-
D.
Phil DeGuere
Phil DeGuere was an American television producer, writer, and director best known for his work on series such as Simon & Simon and the 1980s revival of The Twilight Zone.
-
E.
Greg Glienna
Greg Glienna is an American filmmaker, screenwriter, and actor best known for creating the original characters and story that inspired the "Meet the Parents" film series.
- 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_69d86da94ccc819083d187f5dc6a123e |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e15755b5548190acfa29eecb11e675 |
completed | April 16, 2026, 9:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00dbf46cf881909f6c16f7a3d9a535 |
completed | May 10, 2026, 7:26 p.m. |
| NEDg | Description generation | batch_6a0114d33cac819083d8e542ea5bc274 |
completed | May 10, 2026, 11:29 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0115c967b0819088e2335fd45d755b |
completed | May 10, 2026, 11:33 p.m. |
Created at: April 10, 2026, 4:54 a.m.