Triple
T21536952
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Please Stand By |
E531372
|
entity |
| Predicate | basedOnWorkAuthor |
P2806
|
FINISHED |
| Object | Michael Golamco |
—
|
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: Michael Golamco | Statement: [Please Stand By, basedOnWorkAuthor, Michael Golamco]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Michael Golamco Context triple: [Please Stand By, basedOnWorkAuthor, Michael Golamco]
-
A.
Michael Golamco
chosen
Michael Golamco is an American playwright and screenwriter known for his work in film, television, and theater, often exploring Asian American experiences and contemporary relationships.
-
B.
Andrew Goczkowski
Andrew Goczkowski is an American local government leader serving as the mayor of Des Plaines, Illinois.
-
C.
Michael Elkins
Michael Elkins was a screenwriter known for his work on the 1960 biblical epic film "Esther and the King."
-
D.
Michael Gilio
Michael Gilio is an American screenwriter and filmmaker best known for co-writing the fantasy adventure film "Dungeons & Dragons: Honor Among Thieves."
-
E.
Michael Begler
Michael Begler is an American television writer and producer best known for co-creating the period medical drama series "The Knick."
- 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_69e0c45e5b8881908ac18fc2f493b114 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ee9d0e5a9c8190894ec3666d3296aa |
completed | April 26, 2026, 11:17 p.m. |
Created at: April 16, 2026, 6:27 p.m.