Triple
T8010182
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thomas Kostura |
E186467
|
entity |
| Predicate | caseSubject |
P58780
|
FINISHED |
| Object | same-sex marriage recognition in Tennessee |
—
|
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 marriage recognition in Tennessee | Statement: [Thomas Kostura, caseSubject, same-sex marriage recognition in Tennessee]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: caseSubject Context triple: [Thomas Kostura, caseSubject, same-sex marriage recognition in Tennessee]
-
A.
subjectCanBe
Indicates that the subject has the potential or capability to assume, become, or be classified as the specified object or state.
-
B.
subjectMatter
Indicates the topic, theme, or content area that something (such as a work, document, or discussion) is about.
-
C.
subjectType
Indicates the classification or category that defines what kind of entity the subject is.
-
D.
centralToCase
chosen
Indicates that something plays a pivotal or essential role in determining the outcome or understanding of a particular case.
-
E.
letterCase
Indicates the relationship between a character or string and its typographical case (such as uppercase, lowercase, or mixed case).
- 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_69ca82abaffc8190ab8af79cdbc31ab3 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3d70caf8819090a9f98025470c0d |
completed | March 31, 2026, 3:20 a.m. |
| PD | Predicate disambiguation | batch_69cb048c9f488190b4fb8917a9c21bc5 |
completed | March 30, 2026, 11:17 p.m. |
Created at: March 30, 2026, 5:19 p.m.