Triple
T8295490
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Suffolk University |
E194203
|
entity |
| Predicate | hasLawSchoolRankingSpecialty |
P82583
|
FINISHED |
| Object | legal writing |
—
|
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: legal writing | Statement: [Suffolk University, hasLawSchoolRankingSpecialty, legal writing]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLawSchoolRankingSpecialty Context triple: [Suffolk University, hasLawSchoolRankingSpecialty, legal writing]
-
A.
lawSchoolRankingContext
Indicates the contextual ranking information associated with a law school, such as its position or status within a specified ranking system or timeframe.
-
B.
majorSchoolOfLaw
Indicates that a particular school of law is a primary or dominant legal tradition or framework associated with an entity.
-
C.
containsLawSchool
Indicates that one entity includes or encompasses a law school as part of its structure, contents, or composition.
-
D.
lawSchoolName
Indicates the name of the law school with which an entity (such as a person or institution) is associated.
-
E.
associatedSchoolOfLaw
Indicates a relationship where an entity is connected or linked to a particular school of law, typically as its legal education institution or legal academic affiliation.
- 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_69ca82e50ebc81909aa7b260c76bd757 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb7df73d4c81909ad9cf0786eb5a20 |
completed | March 31, 2026, 7:55 a.m. |
| PD | Predicate disambiguation | batch_69cb70b5b5348190b296e0ecec95de60 |
completed | March 31, 2026, 6:59 a.m. |
| PDg | Predicate description generation | batch_69cb76d648988190ab0669cc0592e827 |
completed | March 31, 2026, 7:25 a.m. |
Created at: March 30, 2026, 5:53 p.m.