Triple
T1440753
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lobos |
E31063
|
entity |
| Predicate | studentSectionReputation |
P29346
|
FINISHED |
| Object | loud |
—
|
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: loud | Statement: [Lobos, studentSectionReputation, loud]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: studentSectionReputation Context triple: [Lobos, studentSectionReputation, loud]
-
A.
studentSection
Indicates a relationship where a student is enrolled in or associated with a particular course section.
-
B.
youthAcademyReputation
Indicates the perceived quality and success of an organization’s youth development system in producing and nurturing young talent.
-
C.
studentSectionName
Indicates that a given student is associated with a specific class section identified by its name.
-
D.
studentSectionNickname
Indicates that a particular nickname is used to refer to a specific student section.
-
E.
hasStudentSection
Indicates that an entity (such as a course or class) is associated with a specific student section or subgroup of enrolled students.
- 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_69a4991633388190a4d61b5a98aa407a |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c5ff8dbc81909eafcfc9f2260a22 |
completed | March 1, 2026, 11:04 p.m. |
| PD | Predicate disambiguation | batch_69a4c478f65481909ee716791c663491 |
completed | March 1, 2026, 10:58 p.m. |
| PDg | Predicate description generation | batch_69a4c5fd2c5c81909283b7a74aff89b7 |
completed | March 1, 2026, 11:04 p.m. |
Created at: March 1, 2026, 8 p.m.