Triple
T10555986
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alexander John Buckley Ford |
E249086
|
entity |
| Predicate | hasFamilyType |
P35173
|
FINISHED |
| Object | same-sex parents |
—
|
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: same-sex parents | Statement: [Alexander John Buckley Ford, hasFamilyType, same-sex parents]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFamilyType Context triple: [Alexander John Buckley Ford, hasFamilyType, same-sex parents]
-
A.
containsFamily
Indicates that one entity includes or encompasses members of a particular family group within it.
-
B.
hasHouseholdType
chosen
Indicates the type or category of household associated with an entity (e.g., family, single-person, shared, etc.).
-
C.
hasFamilyRole
Indicates that one entity holds a specific familial role or position in relation to another entity.
-
D.
hasRepresentativeFamily
Indicates that an entity is associated with a particular family that serves as its representative or characteristic example.
-
E.
hasFamilyNameOf
Indicates that one entity bears or uses the same family name (surname) as another entity.
- 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_69d381c733c08190ab1dd6239f5f34ae |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d52712a9988190bf63e7c47f6e6fc1 |
completed | April 7, 2026, 3:47 p.m. |
| PD | Predicate disambiguation | batch_69d518fa0b4081909bffc936d78bd77b |
completed | April 7, 2026, 2:47 p.m. |
Created at: April 6, 2026, 12:35 p.m.