Triple
T33478423
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lydia Bennet |
E857388
|
entity |
| Predicate | ageAtNovelStart |
P67527
|
FINISHED |
| Object | About 15–16 years old |
—
|
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: About 15–16 years old | Statement: [Lydia Bennet, ageAtNovelStart, About 15–16 years old]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ageAtNovelStart Context triple: [Lydia Bennet, ageAtNovelStart, About 15–16 years old]
-
A.
ageAtEpilogue
Indicates the age of an entity at the time of the epilogue of a narrative or event.
-
B.
ageDuringNarration
chosen
Indicates that an entity has a specified age at the time when the described narrative or event is taking place.
-
C.
ageAtStartOfRole
Indicates the age an entity was when they first began a specified role or position.
-
D.
ageAtIntroduction
Indicates the age an entity had at the time it was first introduced or presented in a given context.
-
E.
protagonistAge
Indicates the age of the main character or central figure in a narrative or scenario.
- 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_69f3497472508190b300ebd3fd402367 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f6e52c1a848190b35743f9e5361969 |
completed | May 3, 2026, 6:03 a.m. |
| PD | Predicate disambiguation | batch_69f6e3da41948190a4cfe866ce184f73 |
completed | May 3, 2026, 5:57 a.m. |
Created at: May 1, 2026, 1:38 a.m.