Triple
T37201690
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Louisa Molesworth |
E922053
|
entity |
| Predicate | hasInLawFamily |
P51928
|
FINISHED |
| Object | Ponsonby family |
—
|
NE NERFINISHED |
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: Ponsonby family | Statement: [Louisa Molesworth, hasInLawFamily, Ponsonby family]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasInLawFamily Context triple: [Louisa Molesworth, hasInLawFamily, Ponsonby family]
-
A.
inLaw
chosen
Indicates a familial relationship created through marriage, such as between a spouse and their partner’s relatives or between relatives of two spouses.
-
B.
hasNameInLaw
Indicates that an entity is known or designated by a specific official or legal name within a law or legal context.
-
C.
hasFamilySituation
Indicates the familial status or circumstances that apply to an entity, such as their family composition, responsibilities, or living situation.
-
D.
hasFamilialTieTo
Indicates a relationship where two entities are connected by family bonds, such as by blood, marriage, or adoption.
-
E.
belongsToLegalFamily
Indicates that one entity is a member of, or is legally affiliated with, a particular legal family or legal system tradition.
- 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_69f76ea4849481909b4a3073efb0114c |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_6a00d9717a9881908194163d719f14d6 |
completed | May 10, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a00d91db2ec81909ebacfc9f0d11dd8 |
completed | May 10, 2026, 7:14 p.m. |
Created at: May 3, 2026, 4:15 p.m.