Triple
T14878492
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Richard Fish |
E349930
|
entity |
| Predicate | portrayedBy |
P1507
|
FINISHED |
| Object | Greg Germann |
E349927
|
NE FINISHED |
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: Greg Germann | Statement: [Richard Fish, portrayedBy, Greg Germann]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Greg Germann Context triple: [Richard Fish, portrayedBy, Greg Germann]
-
A.
Greg Germann
chosen
Greg Germann is an American actor best known for his role as the uptight, comedic lawyer Richard Fish on the television series "Ally McBeal."
-
B.
Mark Bittner
Mark Bittner is an American writer and former street musician best known for his close relationship with and documentation of a flock of wild parrots in San Francisco’s Telegraph Hill neighborhood.
-
C.
Greg Garbowsky
Greg Garbowsky is an American musician and songwriter best known as the longtime bassist and collaborator for the Jonas Brothers.
-
D.
Mark Geiger
Mark Geiger is a retired American soccer referee known for officiating at Major League Soccer’s highest levels and multiple FIFA World Cups.
-
E.
Matt Greenberg
Matt Greenberg is a screenwriter and film producer known for his work on various horror and thriller projects in American cinema.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d822ee4f408190b6ac3b2fa434f0df |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69ded5e4e4448190a8796573bc6d1069 |
completed | April 15, 2026, 12:03 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe9687a5888190a6e6ffd781f64edc |
completed | May 9, 2026, 2:05 a.m. |
Created at: April 10, 2026, 1:55 a.m.