Triple
T24438041
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Virginia Galilei |
E616177
|
entity |
| Predicate | ageAtEnteringConvent |
P109429
|
FINISHED |
| Object | 13 |
—
|
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: 13 | Statement: [Virginia Galilei, ageAtEnteringConvent, 13]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ageAtEnteringConvent Context triple: [Virginia Galilei, ageAtEnteringConvent, 13]
-
A.
enteredConventAt
chosen
Indicates the point in time or age at which a person formally joined or was admitted into a convent.
-
B.
enteredConvent
Indicates that a person has joined and been admitted into a religious convent as a member.
-
C.
tookReligiousVowsOn
Indicates that an entity formally committed to religious vows on a specific date or occasion.
-
D.
tookReligiousVows
Indicates that an entity formally committed to a religious life by taking recognized vows within a religious tradition.
-
E.
foundedAsConventFor
Indicates that an institution or building was originally established specifically to serve as a convent for a particular religious community or group.
- 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_69e2d7ec44b081909ccaf1f3bbec0641 |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f297881fa08190b82bdc5ebeae96f7 |
completed | April 29, 2026, 11:43 p.m. |
| PD | Predicate disambiguation | batch_69f287d3237c819099559c00f83131d8 |
completed | April 29, 2026, 10:36 p.m. |
Created at: April 18, 2026, 2:16 a.m.