Triple
T1110529
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MC |
E25585
|
entity |
| Predicate | postnominalUsage |
P1610
|
FINISHED |
| Object | placed after the recipient’s name |
—
|
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: placed after the recipient’s name | Statement: [MC, postnominalUsage, placed after the recipient’s name]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: postnominalUsage Context triple: [MC, postnominalUsage, placed after the recipient’s name]
-
A.
postNominalLetters
Indicates that a person is associated with specific letters placed after their name to denote qualifications, honors, or professional affiliations.
-
B.
hasPostNominal
chosen
Indicates that an entity is associated with a post-nominal title, abbreviation, or letters that follow a name to denote qualifications, honors, or status.
-
C.
hasPostnominalLetters
Indicates that a person holds specific postnominal letters (abbreviations after their name) signifying qualifications, honors, or titles.
-
D.
postNominalCategory
Indicates a classification or type assigned to an entity that is expressed in a post-nominal position (after the name or noun).
-
E.
namedAfter
Indicates that one entity has been given its name in honor of, or derived from, another entity.
- 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_69a49428d4448190b3b36991ceae87ce |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bbd92a8c8190a16e55f3f739010f |
completed | March 1, 2026, 10:21 p.m. |
| PD | Predicate disambiguation | batch_69a4bb42990c819080db96478fd4977e |
completed | March 1, 2026, 10:18 p.m. |
Created at: March 1, 2026, 7:43 p.m.