Triple
T14229938
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Troisier's sign |
E352724
|
entity |
| Predicate | hasTypicalCourse |
P113303
|
FINISHED |
| Object | painless lymph node enlargement |
—
|
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: painless lymph node enlargement | Statement: [Troisier's sign, hasTypicalCourse, painless lymph node enlargement]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypicalCourse Context triple: [Troisier's sign, hasTypicalCourse, painless lymph node enlargement]
-
A.
typicalCourse
Indicates that one entity is a standard or commonly taken course associated with another entity, such as a program, curriculum, or field of study.
-
B.
hasPrimaryCourse
Indicates that an entity is associated with its main or principal course in a given context (such as a meal, curriculum, or sequence of offerings).
-
C.
hasCoursePattern
Indicates that an entity follows, is associated with, or is defined by a particular course structure or pattern.
-
D.
hasMultipleCourses
Indicates that an entity is associated with more than one course within the given context.
-
E.
isCourse
Indicates that an entity functions as or qualifies as a course within a given context or system.
- 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_69d8278adc7c8190a9218d69bce3c4e6 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de622b89fc8190af08dab9e1976759 |
completed | April 14, 2026, 3:50 p.m. |
| PD | Predicate disambiguation | batch_69de05bf069c8190b69f00f00f5eb126 |
completed | April 14, 2026, 9:15 a.m. |
| PDg | Predicate description generation | batch_69de239a02e881909b0e2679487e4ab2 |
completed | April 14, 2026, 11:23 a.m. |
Created at: April 10, 2026, 1:07 a.m.