Triple
T554705
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mary Howard Darwin |
E11916
|
entity |
| Predicate | notableRelation |
P367
|
FINISHED |
| Object | grandmother-in-law 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: grandmother-in-law of Charles Darwin | Statement: [Mary Howard Darwin, notableRelation, grandmother-in-law of Charles Darwin]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableRelation Context triple: [Mary Howard Darwin, notableRelation, grandmother-in-law of Charles Darwin]
-
A.
notableRelative
chosen
Indicates that an entity has a relative who is notable or well-known, specifying that familial relationship.
-
B.
notablyAssociatedWith
Indicates that one entity is prominently or distinctively connected with another in a way that is especially noteworthy or remarkable.
-
C.
notableFor
Indicates that an entity is especially recognized or distinguished for a particular quality, achievement, characteristic, or role.
-
D.
notableWorkSubject
Indicates that a work is notably associated with a particular subject, such as a person, topic, or entity, as its primary focus or theme.
-
E.
notableFact
Indicates that there exists a particularly significant or noteworthy fact or piece of information associated with the subject.
- 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_69a4932941d08190815efd422f0b4ca7 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a4991c524481908b2bb88c4feabec6 |
completed | March 1, 2026, 7:53 p.m. |
| PD | Predicate disambiguation | batch_69a494bc1f8c8190904356f3a8e801de |
completed | March 1, 2026, 7:34 p.m. |
Created at: March 1, 2026, 7:32 p.m.