Triple
T641229
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Twenty Years After |
E16742
|
entity |
| Predicate | protagonistAgeRelativeToPrequel |
P17626
|
FINISHED |
| Object | older by twenty years |
—
|
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: older by twenty years | Statement: [Twenty Years After, protagonistAgeRelativeToPrequel, older by twenty years]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: protagonistAgeRelativeToPrequel Context triple: [Twenty Years After, protagonistAgeRelativeToPrequel, older by twenty years]
-
A.
protagonistNationality
Indicates the country or national identity to which the protagonist of a work is associated or belongs.
-
B.
mainProtagonist
Indicates that the subject is the central character or primary focus in the narrative of the related work.
-
C.
sequelReleaseYear
Indicates the calendar year in which a sequel to an original work is released.
-
D.
hasProtagonist
Indicates that a work of narrative has a main character who serves as its central focus or driving agent.
-
E.
hasSequel
Indicates that one work is followed by another work that continues its story, timeline, or thematic development.
- F. None of above. chosen
Provenance (4 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_69a4936be1c88190af56540324b57da7 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a49f02bc2c8190b8a92b2505768c19 |
completed | March 1, 2026, 8:18 p.m. |
| PD | Predicate disambiguation | batch_69a49d0830008190a26ee158ed4dd1fe |
completed | March 1, 2026, 8:09 p.m. |
| PDg | Predicate description generation | batch_69a49df0de3c81909721eb391ec94031 |
completed | March 1, 2026, 8:13 p.m. |
Created at: March 1, 2026, 7:36 p.m.