Triple
T13274146
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Panic in Year Zero! |
E316142
|
entity |
| Predicate | mainCharacter |
P1183
|
FINISHED |
| Object | Ann Baldwin |
E438885
|
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: Ann Baldwin | Statement: [Panic in Year Zero!, mainCharacter, Ann Baldwin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ann Baldwin Context triple: [Panic in Year Zero!, mainCharacter, Ann Baldwin]
-
A.
Karen Baldwin
Karen Baldwin is a central character in the alternate-history space drama series "For All Mankind," known for her complex personal journey amid the political and emotional fallout of the space race.
-
B.
Karen Baldwin
Karen Baldwin is a film producer best known for her work on the Oscar-winning biographical drama "Ray."
-
C.
Anne Caldwell
Anne Caldwell is an author known for writing the book "Sunny."
-
D.
April Blair
April Blair is an American television writer and producer best known for developing and executive producing the drama series "All American."
-
E.
Mary Beth Hughes
chosen
Mary Beth Hughes was an American film and television actress best known for her roles in 1940s Hollywood dramas and crime films.
- 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_69d806b1d9ac8190852c5571d5bd5f0f |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d9904193bc8190af4155750bcf32f6 |
completed | April 11, 2026, 12:05 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd19226eb881908f76134a04e72548 |
completed | May 7, 2026, 10:58 p.m. |
Created at: April 9, 2026, 9:26 p.m.