Triple
T13661910
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thérèse of Lisieux |
E327017
|
entity |
| Predicate | ageAtEntranceToCarmel |
P111043
|
FINISHED |
| Object | 15 |
—
|
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: 15 | Statement: [Thérèse of Lisieux, ageAtEntranceToCarmel, 15]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ageAtEntranceToCarmel Context triple: [Thérèse of Lisieux, ageAtEntranceToCarmel, 15]
-
A.
typicallyIssuedAtAge
Indicates the age at which something is most commonly or customarily issued to an individual.
-
B.
ageAtIntroduction
Indicates the age an entity had at the time it was first introduced or presented in a given context.
-
C.
ageAtConversion
Indicates the age an entity was when a specified conversion event (such as a change of status, belief, or state) occurred.
-
D.
containsAge
Indicates that one entity includes or specifies the age value or age-related information of another entity.
-
E.
cameOfAge
Indicates that an entity reached the age or stage of maturity at which it is considered an adult or fully responsible.
- 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_69d8076d8270819092afc2f0e9c359a8 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbc620df208190afaccf3ddd10aa60 |
completed | April 12, 2026, 4:19 p.m. |
| PD | Predicate disambiguation | batch_69dbbe8a027081908d8f884b89707a5e |
completed | April 12, 2026, 3:47 p.m. |
| PDg | Predicate description generation | batch_69dbc59ca1a88190a6abd3bd00554c93 |
completed | April 12, 2026, 4:17 p.m. |
Created at: April 9, 2026, 9:52 p.m.