Triple
T461064
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Juris Doctor |
E7336
|
entity |
| Predicate | commonPostNominalLetters |
P1804
|
FINISHED |
| Object | J.D. |
—
|
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: J.D. | Statement: [Juris Doctor, commonPostNominalLetters, J.D.]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: commonPostNominalLetters Context triple: [Juris Doctor, commonPostNominalLetters, J.D.]
-
A.
postNominalLetters
Indicates that a person is associated with specific letters placed after their name to denote qualifications, honors, or professional affiliations.
-
B.
hasPostnominalLetters
chosen
Indicates that a person holds specific postnominal letters (abbreviations after their name) signifying qualifications, honors, or titles.
-
C.
usesAdditionalLettersFrom
Indicates that one entity forms or derives its representation by incorporating extra letters taken from another entity beyond those originally present.
-
D.
hasPostNominal
Indicates that an entity is associated with a post-nominal title, abbreviation, or letters that follow a name to denote qualifications, honors, or status.
-
E.
firstLetter
Indicates that one entity is the initial character or starting letter of another entity (typically a string or word).
- 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_69a2e7e5c5bc8190a1dc8178218fba40 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2efbed5b88190a45716812eb4cfdf |
completed | Feb. 28, 2026, 1:38 p.m. |
| PD | Predicate disambiguation | batch_69a2ede75b6c81908350103d21f22a03 |
completed | Feb. 28, 2026, 1:30 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.