Triple
T9741596
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Avenue 5 |
E236197
|
entity |
| Predicate | hasCastMember |
P2308
|
FINISHED |
| Object | Zach Woods |
E226118
|
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: Zach Woods | Statement: [Avenue 5, hasCastMember, Zach Woods]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Zach Woods Context triple: [Avenue 5, hasCastMember, Zach Woods]
-
A.
Zach Woods
chosen
Zach Woods is an American actor and comedian best known for his roles on television series such as "The Office," "Silicon Valley," and "Avenue 5."
-
B.
Zach Staenberg
Zach Staenberg is an American film editor best known for his Academy Award–winning work on "The Matrix" and its sequels.
-
C.
Dan Fogler
Dan Fogler is an American actor and comedian best known for roles in films like "Fantastic Beasts" and "Balls of Fury" as well as his work on stage and in voice acting.
-
D.
Ike Barinholtz
Ike Barinholtz is an American actor, comedian, writer, and director known for his work on the TV series "The Mindy Project" and films such as "Neighbors" and "Blockers."
-
E.
Michael Urie
Michael Urie is an American actor best known for his role as Marc St. James on the television series "Ugly Betty" and for his extensive work in theater and film.
- 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_69ca84d3e24481908a476e2231123cf9 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cd9f2af3e48190b83a442cd0e84062 |
completed | April 1, 2026, 10:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1bccf62e08190ae799ee557ad1f1b |
completed | April 5, 2026, 1:37 a.m. |
Created at: March 30, 2026, 8:23 p.m.