Triple
T31105
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Notorious RBG |
E620
|
entity |
| Predicate | honors |
P2354
|
FINISHED |
| Object | Ruth Bader Ginsburg’s judicial legacy |
—
|
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: Ruth Bader Ginsburg’s judicial legacy | Statement: [Notorious RBG, honors, Ruth Bader Ginsburg’s judicial legacy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: honors Context triple: [Notorious RBG, honors, Ruth Bader Ginsburg’s judicial legacy]
-
A.
honorLevel
Indicates the degree or status of respect, distinction, or recognition accorded to an entity relative to others.
-
B.
honorificRank
Indicates that one entity holds a formal title or honorific status in relation to another entity.
-
C.
awardFor
Indicates that something is given or granted as recognition or a prize for a particular achievement, work, or contribution.
-
D.
honorificSuffix
Indicates that one entity is a respectful or formal suffix appended to another entity’s name or title.
-
E.
awardStatus
Indicates the current state or outcome of an award in relation to an entity, such as whether it has been granted, pending, rejected, or completed.
- 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_69a2479dec388190967ba648663442c9 |
completed | Feb. 28, 2026, 1:40 a.m. |
| NER | Named-entity recognition | batch_69a249ec0d288190ac3a0939db61813b |
completed | Feb. 28, 2026, 1:50 a.m. |
| PD | Predicate disambiguation | batch_69a24870417081909c7c01e400c94716 |
completed | Feb. 28, 2026, 1:44 a.m. |
| PDg | Predicate description generation | batch_69a249eb52a08190916849b44bd9d68d |
completed | Feb. 28, 2026, 1:50 a.m. |
Created at: Feb. 28, 2026, 1:44 a.m.