Triple
T15019989
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anomalisa |
E378057
|
entity |
| Predicate | voiceActor |
P1507
|
FINISHED |
| Object | Tom Noonan |
E148080
|
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: Tom Noonan | Statement: [Anomalisa, voiceActor, Tom Noonan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tom Noonan Context triple: [Anomalisa, voiceActor, Tom Noonan]
-
A.
Tom Noonan
chosen
Tom Noonan is an American character actor, writer, and director known for his distinctive, often menacing roles in films such as "Manhunter," "Last Action Hero," and "Synecdoche, New York."
-
B.
Kevin Edward Noonan
Kevin Edward Noonan is the former husband of U.S. Supreme Court Justice Sonia Sotomayor, to whom she was married from 1976 to 1983.
-
C.
Danny Noonan
Danny Noonan is the young, ambitious golf caddie who serves as the central protagonist in the comedy film "Caddyshack."
-
D.
Tom Doherty
Tom Doherty is an American publisher best known as the founder of the science fiction and fantasy imprint Tor Books.
-
E.
Peter O’Neill
Peter O’Neill is a Papua New Guinean politician who served as Prime Minister of Papua New Guinea from 2011 to 2019.
- 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_69d85cd3a3c881908c71fc424d459c17 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded76445988190984b57de66e00c4a |
completed | April 15, 2026, 12:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0167369d9481909015c34d475fac14 |
completed | May 11, 2026, 5:20 a.m. |
Created at: April 10, 2026, 2:56 a.m.