Triple
T1362389
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | DeBoer v. Snyder |
E29124
|
entity |
| Predicate | originalFocus |
P31
|
FINISHED |
| Object | second-parent adoption by same-sex couple |
—
|
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: second-parent adoption by same-sex couple | Statement: [DeBoer v. Snyder, originalFocus, second-parent adoption by same-sex couple]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: originalFocus Context triple: [DeBoer v. Snyder, originalFocus, second-parent adoption by same-sex couple]
-
A.
focusesOn
chosen
Indicates that one entity directs its attention, effort, or primary activity toward another entity or specific subject.
-
B.
primaryTarget
Indicates that an entity is the main or most important target of another entity’s action, focus, or effect.
-
C.
primaryFront
Indicates that one entity serves as the main or most important front-facing side or surface in relation to another entity.
-
D.
mayProvideFocus
Indicates that one entity can potentially direct attention, emphasis, or concentration toward another entity or aspect.
-
E.
originalForm
Indicates that one entity is the earlier, source, or initial version from which another entity is derived or transformed.
- 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_69a498d77abc8190913bf57e5f51d2c4 |
completed | March 1, 2026, 7:51 p.m. |
| NER | Named-entity recognition | batch_69a4c2b4ab3c8190ad692e32eee05976 |
completed | March 1, 2026, 10:50 p.m. |
| PD | Predicate disambiguation | batch_69a4bef945c08190a027472fdd695ea5 |
completed | March 1, 2026, 10:34 p.m. |
Created at: March 1, 2026, 7:57 p.m.