Triple
T12947426
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Life as We Know It |
E309805
|
entity |
| Predicate | editedBy |
P1954
|
FINISHED |
| Object | Jim Page |
E351037
|
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: Jim Page | Statement: [Life as We Know It, editedBy, Jim Page]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jim Page Context triple: [Life as We Know It, editedBy, Jim Page]
-
A.
Jim Page
chosen
Jim Page is a film editor known for his work on the neo-noir black comedy crime film "Kiss Kiss Bang Bang."
-
B.
David Gilroy Bevan
David Gilroy Bevan was a British industrial chemist and academic known for his contributions to inorganic chemistry and crystallography.
-
C.
Doug McKendall
Doug McKendall is a technology entrepreneur best known as a founder of the cybersecurity and software company Symantec.
-
D.
Ian Kennedy Martin
Ian Kennedy Martin is a British television scriptwriter and producer known for creating the long-running police drama series "The Sweeney."
-
E.
Peter Templeman
Peter Templeman is an Australian film director and screenwriter known for his work on acclaimed short films and television projects.
- 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_69d7bdfb57a88190836b743e2825feca |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d97e1c67b8819094e5243267f93ce2 |
completed | April 10, 2026, 10:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6af75bc04819098d98c47fca48ac9 |
completed | May 3, 2026, 2:14 a.m. |
Created at: April 9, 2026, 5:43 p.m.