Triple
T21780774
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bonjour Tristesse (film) |
E537704
|
entity |
| Predicate | mainProtagonistAge |
P37051
|
FINISHED |
| Object | teenager |
—
|
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: teenager | Statement: [Bonjour Tristesse (film), mainProtagonistAge, teenager]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainProtagonistAge Context triple: [Bonjour Tristesse (film), mainProtagonistAge, teenager]
-
A.
protagonistAge
chosen
Indicates the age of the main character or central figure in a narrative or scenario.
-
B.
mainProtagonist
Indicates that the subject is the central character or primary focus in the narrative of the related work.
-
C.
protagonistAgeRelativeToPrequel
Indicates how the protagonist’s age in the current work compares to their age in a preceding prequel story.
-
D.
hasProtagonistAgeRange
Indicates that a work’s main character falls within a specified age range.
-
E.
hasChildProtagonist
Indicates that the work features a child as its main or central character.
- 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_69e0c470759c819094a215757113562b |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69f0462cae6481908d3e7f71683d8921 |
completed | April 28, 2026, 5:31 a.m. |
| PD | Predicate disambiguation | batch_69e6be6299988190a34c98fa76d94700 |
completed | April 21, 2026, 12:01 a.m. |
Created at: April 16, 2026, 6:52 p.m.