Triple
T5853215
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Henry J. Friendly |
E130086
|
entity |
| Predicate | lawReviewPosition |
P5610
|
FINISHED |
| Object | president of the Harvard Law Review |
—
|
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: president of the Harvard Law Review | Statement: [Henry J. Friendly, lawReviewPosition, president of the Harvard Law Review]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lawReviewPosition Context triple: [Henry J. Friendly, lawReviewPosition, president of the Harvard Law Review]
-
A.
legalProfessionRole
chosen
Indicates that one entity holds or performs a specific professional role within the legal domain in relation to another entity or context.
-
B.
lawReview
Indicates a relationship where an entity is associated with a law review, typically as its subject, source, or venue of publication within legal scholarship.
-
C.
positionOnLaw
Indicates a stance, opinion, or interpretation that an entity holds regarding a specific law or legal provision.
-
D.
lawJournal
Indicates a relationship where a work is published in, associated with, or appears within a specific law journal.
-
E.
legalSystemRole
Indicates the specific function, capacity, or position an entity holds within a legal or judicial system.
- 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_69c0084de39081909eb34e6bed74215a |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c044ab0a048190b84be40fb13c0f50 |
completed | March 22, 2026, 7:36 p.m. |
| PD | Predicate disambiguation | batch_69c03345ca0c819081c81148d054fed2 |
completed | March 22, 2026, 6:21 p.m. |
Created at: March 22, 2026, 3:55 p.m.