Triple
T13522725
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Margene Heffman |
E322939
|
entity |
| Predicate | ageRelativeToOtherWives |
P110675
|
FINISHED |
| Object | youngest |
—
|
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: youngest | Statement: [Margene Heffman, ageRelativeToOtherWives, youngest]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ageRelativeToOtherWives Context triple: [Margene Heffman, ageRelativeToOtherWives, youngest]
-
A.
spouseAgeDifference
Indicates the age gap between two individuals who are spouses in a marital relationship.
-
B.
spouseCount
Indicates the number of spouses an entity has.
-
C.
hasSpouseInStory
Indicates that one entity is depicted as the spouse of another within the context of a particular story or narrative.
-
D.
numberOfMarriagesOfSpouse
Indicates the total count of times the referenced spouse has been married.
-
E.
spouseDynasty
Indicates that there is a marital relationship linking an entity to the dynasty (family line or ruling house) of their spouse.
- 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_69d80766a21881909f21a1b7421d3b8a |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbafa535cc81908d0018fef81a2848 |
completed | April 12, 2026, 2:43 p.m. |
| PD | Predicate disambiguation | batch_69dbae1046c48190b4ee98c6c9cb9d85 |
completed | April 12, 2026, 2:37 p.m. |
| PDg | Predicate description generation | batch_69dbaecc98cc8190829f5be759c4f1e3 |
completed | April 12, 2026, 2:40 p.m. |
Created at: April 9, 2026, 9:44 p.m.