Triple
T185955
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Robert E. Lee |
E3980
|
entity |
| Predicate | classRankAtGraduation |
P1944
|
FINISHED |
| Object | second in his class |
—
|
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: second in his class | Statement: [Robert E. Lee, classRankAtGraduation, second in his class]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: classRankAtGraduation Context triple: [Robert E. Lee, classRankAtGraduation, second in his class]
-
A.
academicDegree
Indicates that an entity holds or has been awarded a specific academic degree.
-
B.
college
Indicates that an entity is a college-level educational institution attended by or associated with another entity.
-
C.
educatedAt
Indicates that an entity received education or formal training at a specified institution or place of learning.
-
D.
orderGradeLevel
Indicates the relative sequencing or ranking of grade levels, specifying which grade comes before or after another.
-
E.
rankedAs
chosen
Indicates that one entity is assigned a specific position or level in an ordered ranking relative to others.
- 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_69a25497e2f08190a040f8c6e1842643 |
completed | Feb. 28, 2026, 2:36 a.m. |
| NER | Named-entity recognition | batch_69a2594809288190b3d3b1283e7e0d00 |
completed | Feb. 28, 2026, 2:56 a.m. |
| PD | Predicate disambiguation | batch_69a25670feb081908e26a2543ebe7b3a |
completed | Feb. 28, 2026, 2:44 a.m. |
Created at: Feb. 28, 2026, 2:40 a.m.