Triple
T10011171
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dr. Mark Clyne |
E199375
|
entity |
| Predicate | appearsInYearOfWorkRelease |
P29413
|
FINISHED |
| Object | 2016 |
—
|
LITERAL 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: 2016 | Statement: [Dr. Mark Clyne, appearsInYearOfWorkRelease, 2016]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: appearsInYearOfWorkRelease Context triple: [Dr. Mark Clyne, appearsInYearOfWorkRelease, 2016]
-
A.
yearOfFilmAppearance
Indicates the specific year in which a film appearance by an entity took place.
-
B.
playedInYear
chosen
Indicates that an entity participated in or was active in a particular activity, event, or role during a specified calendar year.
-
C.
workReleaseYear
Indicates the calendar year in which a work (such as a book, film, or album) was first released or made publicly available.
-
D.
filmReleaseYear
Indicates the calendar year in which a film was first officially released to the public.
-
E.
notableWorkYear
Indicates the year in which a notable work associated with an entity was created, released, or achieved prominence.
- F. None of above.
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_69ca8315a1a08190ab310f25620f362b |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cdcd3b68888190b8a325b52d57c5b8 |
completed | April 2, 2026, 1:58 a.m. |
| PD | Predicate disambiguation | batch_69cd1da2cf9081908a6c0eb5247d0bc2 |
completed | April 1, 2026, 1:29 p.m. |
Created at: March 30, 2026, 8:52 p.m.