Triple
T1448995
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chris Darwin |
E31243
|
entity |
| Predicate | degreeOfKinship |
P7844
|
FINISHED |
| Object | great-great-grandson of Charles Darwin |
—
|
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: great-great-grandson of Charles Darwin | Statement: [Chris Darwin, degreeOfKinship, great-great-grandson of Charles Darwin]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: degreeOfKinship Context triple: [Chris Darwin, degreeOfKinship, great-great-grandson of Charles Darwin]
-
A.
geneticRelation
Indicates that two entities are connected through a hereditary or familial genetic relationship.
-
B.
relationshipToHumans
Indicates the nature or type of connection, association, or relevance that something has specifically with humans.
-
C.
hasFamilialTieTo
chosen
Indicates a relationship where two entities are connected by family bonds, such as by blood, marriage, or adoption.
-
D.
closestLivingRelatives
Indicates that the related entities are the most closely related to each other among all currently living entities, in terms of evolutionary or genealogical proximity.
-
E.
isNephewOf
Indicates that one person is the male child of another person's sibling.
- 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_69a499171a28819085b993a3ac78e363 |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c55c408c8190917ed44d9070a2fb |
completed | March 1, 2026, 11:01 p.m. |
| PD | Predicate disambiguation | batch_69a4c47a840c819083307a65c027a19e |
completed | March 1, 2026, 10:58 p.m. |
Created at: March 1, 2026, 8 p.m.