Triple
T19391903
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Matilda of Anjou |
E485089
|
entity |
| Predicate | relativeRelation |
P94755
|
FINISHED |
| Object | aunt of Henry II of England |
—
|
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: aunt of Henry II of England | Statement: [Matilda of Anjou, relativeRelation, aunt of Henry II of England]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relativeRelation Context triple: [Matilda of Anjou, relativeRelation, aunt of Henry II of England]
-
A.
laterRelationWith
Indicates that one entity stands in a temporal relationship to another such that it occurs or exists at a later time than the other.
-
B.
subjectRelation
Indicates that one entity stands in a specified relational role or connection to another entity.
-
C.
relationshipToRelative
chosen
Indicates the specific familial connection or kinship role that one person has in relation to a particular relative.
-
D.
termRelationTo
Indicates a general relational association between one term and another, without specifying the exact nature of that relationship.
-
E.
semanticRelation
Indicates a general meaning-based connection between two entities, such as similarity, implication, or conceptual association.
- 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_69d8e8d460d88190abf0591c5c9d2b0c |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e61b45caec81909dafdf66b361effd |
completed | April 20, 2026, 12:25 p.m. |
| PD | Predicate disambiguation | batch_69e4fd602f008190aa9bc76ae17e4ce1 |
completed | April 19, 2026, 4:05 p.m. |
Created at: April 10, 2026, 1:36 p.m.