Triple
T13994036
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amy (2015 documentary film) |
E336649
|
entity |
| Predicate | writer |
P1360
|
FINISHED |
| Object | Chris King |
E493587
|
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: Chris King | Statement: [Amy (2015 documentary film), writer, Chris King]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chris King Context triple: [Amy (2015 documentary film), writer, Chris King]
-
A.
Chris King
chosen
Chris King is an individual known for being the subject of writing by Amy.
-
B.
Tony Martin
Tony Martin is an English heavy metal vocalist best known for his multiple tenures as lead singer of Black Sabbath during the late 1980s and 1990s.
-
C.
Tony Martin
Tony Martin was an American pop singer and actor popular from the 1930s through the 1950s, known for his smooth baritone voice and appearances in numerous Hollywood musicals.
-
D.
Carlos King
Carlos King is a television producer and reality TV showrunner best known for creating and executive producing popular unscripted series.
-
E.
Ian Martin
Ian Martin is a British comedy writer and satirist known for his work on political satires such as the film "The Death of Stalin" and the TV series "The Thick of It."
- 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_69d81c639e808190a0e4b4f3d31c6a59 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2eb53f508190855cd69b8061dd77 |
completed | April 14, 2026, 12:10 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fbac9a7e8c8190a0fd0cd67ff50741 |
completed | May 6, 2026, 9:03 p.m. |
Created at: April 9, 2026, 10:19 p.m.