Triple
T29739763
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Linda Nordley |
E752564
|
entity |
| Predicate | introducedInFilmReleaseYear |
P18082
|
FINISHED |
| Object | 1953 |
—
|
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: 1953 | Statement: [Linda Nordley, introducedInFilmReleaseYear, 1953]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: introducedInFilmReleaseYear Context triple: [Linda Nordley, introducedInFilmReleaseYear, 1953]
-
A.
yearOfFilmAppearance
chosen
Indicates the specific year in which a film appearance by an entity took place.
-
B.
introducedInYear
Indicates the year in which something was first introduced, launched, or made available.
-
C.
reintroducedInYear
Indicates that an entity, previously absent or discontinued, was brought back or reinstated in a specified year.
-
D.
workReleaseYearOfAppearance
Indicates the year in which a particular work was first released or made its initial appearance.
-
E.
yearInception
Indicates the year in which something (such as an entity, event, or organization) was first established, created, or began.
- 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_69f0d62b064081908c1ae61cd68fb139 |
completed | April 28, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69fbaebc8f2c8190b94f1b4a3ec92e8c |
completed | May 6, 2026, 9:12 p.m. |
| PD | Predicate disambiguation | batch_69fbadf1e6008190a71bbd196ba06844 |
completed | May 6, 2026, 9:09 p.m. |
Created at: April 28, 2026, 7:47 p.m.