Triple
T19328532
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Philip Jennings |
E483422
|
entity |
| Predicate | neighborOf |
P350
|
FINISHED |
| Object | Stan Beeman |
—
|
NE NERFINISHED |
How this triple was built (2 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: Stan Beeman | Statement: [Philip Jennings, neighborOf, Stan Beeman]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Stan Beeman Context triple: [Philip Jennings, neighborOf, Stan Beeman]
-
A.
Stan Beeman
chosen
Stan Beeman is a troubled but dedicated FBI counterintelligence agent and neighbor to the Jennings family in the television series "The Americans."
-
B.
John Beeman
John Beeman was an early Texas settler associated with the pioneering families connected to John Neely Bryan, the founder of Dallas.
-
C.
Greg Beeman
Greg Beeman is an American television director and producer known for his work on genre series such as "Falling Skies," "Heroes," and "Smallville."
-
D.
Dan Beeman
Dan Beeman is a member of the band Helmet, contributing to the influential American alternative metal group's lineup.
-
E.
Jeff Bierman
Jeff Bierman is a cinematographer best known for his work on the crime thriller film "Emily the Criminal."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e8d13e3c81909d91d1d5ec37c095 |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e6163f32f48190be17cccf4e537372 |
completed | April 20, 2026, 12:04 p.m. |
Created at: April 10, 2026, 1:33 p.m.