Triple
T13516068
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Portrait of a Lady (1996 film) |
E322761
|
entity |
| Predicate | hasAdaptationSourcePublicationYear |
P25
|
FINISHED |
| Object | 1881 |
—
|
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: 1881 | Statement: [The Portrait of a Lady (1996 film), hasAdaptationSourcePublicationYear, 1881]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAdaptationSourcePublicationYear Context triple: [The Portrait of a Lady (1996 film), hasAdaptationSourcePublicationYear, 1881]
-
A.
adaptationReleaseYear
Indicates the year in which an adaptation of a work was released.
-
B.
publicationYear
chosen
Indicates the specific calendar year in which a work was formally published or released.
-
C.
lastPublicationYear
Indicates the year in which an entity’s most recent publication was released.
-
D.
appearsInPublicationYear
Indicates that an entity is featured in a publication that was released in a specific year.
-
E.
hasYearInTitle
Indicates that the title of an entity explicitly contains a year value as part of its text.
- 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_69d80766a21881909f21a1b7421d3b8a |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbafa0ed508190b2855171b1945e84 |
completed | April 12, 2026, 2:43 p.m. |
| PD | Predicate disambiguation | batch_69dbae0b63748190b5e207f84b2532ea |
completed | April 12, 2026, 2:36 p.m. |
Created at: April 9, 2026, 9:44 p.m.