Triple
T14822171
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Carlisle Cullen |
E348476
|
entity |
| Predicate | turnedIntoVampireAtAge |
P115959
|
FINISHED |
| Object | 23 |
—
|
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: 23 | Statement: [Carlisle Cullen, turnedIntoVampireAtAge, 23]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: turnedIntoVampireAtAge Context triple: [Carlisle Cullen, turnedIntoVampireAtAge, 23]
-
A.
ageAtFirstTransformation
Indicates the age an entity was when it underwent its first transformation or change of state.
-
B.
turnedIntoWerewolfBy
Indicates that one entity was transformed into a werewolf as a result of the actions or influence of another entity.
-
C.
becomesImmortalIn
Indicates that an entity transitions into a state of immortality within a specified context, time, or medium.
-
D.
hasAgeTransformation
Indicates a relationship where an entity undergoes or causes a change in age or age-related state.
-
E.
vampireType
Indicates that one entity is classified as a specific type or category of vampire in relation to another entity.
- 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_69d822eb8f588190bf53445e730a934f |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69decfe64328819083ce42704cf0602d |
completed | April 14, 2026, 11:38 p.m. |
| PD | Predicate disambiguation | batch_69de8c13418c819088ff9905ace1416a |
completed | April 14, 2026, 6:48 p.m. |
| PDg | Predicate description generation | batch_69de90806f3881908fcbfec5bd4ab4d2 |
completed | April 14, 2026, 7:07 p.m. |
Created at: April 10, 2026, 1:51 a.m.