Triple
T26491118
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fellow of the American College of Physicians |
E669157
|
entity |
| Predicate | usedAfterNameAs |
P129195
|
FINISHED |
| Object | M.D., FACP |
—
|
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: M.D., FACP | Statement: [Fellow of the American College of Physicians, usedAfterNameAs, M.D., FACP]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedAfterNameAs Context triple: [Fellow of the American College of Physicians, usedAfterNameAs, M.D., FACP]
-
A.
usedAfterName
chosen
Indicates that one element is used or appears immediately after a name in some context or representation.
-
B.
usedAfterNameOf
Indicates that something is used immediately following the mention or specification of a name.
-
C.
namedAfter
Indicates that one entity has been given its name in honor of, or derived from, another entity.
-
D.
usesNameDueTo
Indicates that one entity adopts or applies a particular name for another entity specifically because of some motivating reason, circumstance, or dependency.
-
E.
usedBeforeNameOf
Indicates that one element is used immediately before the name of another element, typically as a prefix or preceding modifier.
- 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_69eeb319007081909642b414b114b35a |
completed | April 27, 2026, 12:51 a.m. |
| NER | Named-entity recognition | batch_69f6b2a65c7c8190ac40f1466ceadefc |
completed | May 3, 2026, 2:27 a.m. |
| PD | Predicate disambiguation | batch_69f6b14d7d508190bc7d4c89dfba4a32 |
completed | May 3, 2026, 2:22 a.m. |
Created at: April 27, 2026, 1:04 a.m.