Triple
T25141970
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saint Etheldreda |
E629825
|
entity |
| Predicate | maintainedVirginityInMarriage |
P158190
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Saint Etheldreda, maintainedVirginityInMarriage, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maintainedVirginityInMarriage Context triple: [Saint Etheldreda, maintainedVirginityInMarriage, true]
-
A.
refersToVirginity
Indicates that something is about or explicitly references the state or concept of virginity.
-
B.
usedBeforeMarriageAs
Indicates that one entity was used by or associated with another entity prior to that entity’s marriage.
-
C.
neverMarried
Indicates that the subject has not been legally married to any partner at any time up to the present.
-
D.
hasAttitudeTowardMarriage
Indicates that an entity holds a particular opinion, feeling, or stance regarding the institution or concept of marriage.
-
E.
marriageChildless
Indicates that a marriage exists in which the spouses have no children.
- 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_69e2ff349e408190a6f4a5a66279f54d |
completed | April 18, 2026, 3:49 a.m. |
| NER | Named-entity recognition | batch_69f46849ab4081909a2278c535b5e5bc |
completed | May 1, 2026, 8:46 a.m. |
| PD | Predicate disambiguation | batch_69f45cfb53f4819099bba48c5057e787 |
completed | May 1, 2026, 7:57 a.m. |
| PDg | Predicate description generation | batch_69f464ae42e88190b3549fdf4e0b425e |
completed | May 1, 2026, 8:30 a.m. |
Created at: April 18, 2026, 6:29 a.m.