Triple
T11327626
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Julie d’Étanges |
E268261
|
entity |
| Predicate | postMarriageRole |
P95303
|
FINISHED |
| Object | moral center of Clarens household |
—
|
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: moral center of Clarens household | Statement: [Julie d’Étanges, postMarriageRole, moral center of Clarens household]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: postMarriageRole Context triple: [Julie d’Étanges, postMarriageRole, moral center of Clarens household]
-
A.
afterMarriageRole
chosen
Indicates the role or status an entity assumes following a marriage event.
-
B.
positionOnMarriage
Indicates a person's stance, opinion, or policy regarding the institution or practice of marriage.
-
C.
marriedAfter
Indicates that one marriage occurred later in time than another specified marriage.
-
D.
roleDuringSpouseTenure
Indicates that a person held a particular role or position specifically during the period when their spouse was in office or serving in a defined tenure.
-
E.
spouseLaterMarriedBy
Indicates that one’s spouse subsequently entered into a later marriage with another partner.
- 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_69d6aacb1f0881908c84a349fd1be047 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e9e2253881909518cad0f12ef612 |
completed | April 9, 2026, 6:03 p.m. |
| PD | Predicate disambiguation | batch_69d787afe5a48190b8af1a3e19529641 |
completed | April 9, 2026, 11:04 a.m. |
Created at: April 8, 2026, 9:32 p.m.