Triple
T2385666
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bridget Jones |
E48815
|
entity |
| Predicate | ageInFirstNovel |
P37051
|
FINISHED |
| Object | early thirties |
—
|
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: early thirties | Statement: [Bridget Jones, ageInFirstNovel, early thirties]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ageInFirstNovel Context triple: [Bridget Jones, ageInFirstNovel, early thirties]
-
A.
fictionalAge
Indicates the age attributed to an entity within a fictional or narrative context, rather than its real-world age.
-
B.
protagonistAge
chosen
Indicates the age of the main character or central figure in a narrative or scenario.
-
C.
yearLit
Indicates the year in which something was illuminated, lit, or first had lighting installed or activated.
-
D.
hasFirstEditionYear
Indicates the year in which the first edition of an item (such as a work, book, or publication) was originally released or published.
-
E.
debutWork
Indicates the work (such as a book, film, album, or performance) that marks an entity’s first public or professional appearance in a given field.
- 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_69a88aa5f63081908d07fd302029fcbd |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc7d8a918819089a210e74e13be6e |
completed | March 7, 2026, 6:38 a.m. |
| PD | Predicate disambiguation | batch_69abc59f73f08190924a36d7d475d8f4 |
completed | March 7, 2026, 6:28 a.m. |
Created at: March 4, 2026, 7:57 p.m.