Triple
T2085319
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sonia Sotomayor |
E45335
|
entity |
| Predicate | graduationYear (Yale Law School) |
P34603
|
FINISHED |
| Object | 1979 |
—
|
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: 1979 | Statement: [Sonia Sotomayor, graduationYear (Yale Law School), 1979]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: graduationYear (Yale Law School) Context triple: [Sonia Sotomayor, graduationYear (Yale Law School), 1979]
-
A.
lawSchoolName
Indicates the name of the law school with which an entity (such as a person or institution) is associated.
-
B.
studiedLawIn
Indicates that a person received legal education or training at a particular institution or location.
-
C.
lawSchoolRankingContext
Indicates the contextual ranking information associated with a law school, such as its position or status within a specified ranking system or timeframe.
-
D.
majorSchoolOfLaw
Indicates that a particular school of law is a primary or dominant legal tradition or framework associated with an entity.
-
E.
trialYear
Indicates the calendar year in which a particular trial takes place or is conducted.
- F. None of above. chosen
Provenance (4 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_69a8891869c88190a02643e3bb746f59 |
completed | March 4, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69abba53d4488190a7d9eabcb6904e8e |
completed | March 7, 2026, 5:40 a.m. |
| PD | Predicate disambiguation | batch_69abb7b4356881909217c42ccb8bb1ed |
completed | March 7, 2026, 5:29 a.m. |
| PDg | Predicate description generation | batch_69abb83e7888819096dc40275c77daff |
completed | March 7, 2026, 5:31 a.m. |
Created at: March 4, 2026, 7:41 p.m.