Triple
T5739330
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Indian Forest Service Examination |
E126574
|
entity |
| Predicate | optionalSubjectsInclude |
P62594
|
FINISHED |
| Object | Forestry |
—
|
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: Forestry | Statement: [Indian Forest Service Examination, optionalSubjectsInclude, Forestry]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: optionalSubjectsInclude Context triple: [Indian Forest Service Examination, optionalSubjectsInclude, Forestry]
-
A.
hasSecondarySubject
Indicates that an entity is associated with an additional, non-primary subject in a given context or relationship.
-
B.
curriculumIncluded
chosen
Indicates that a particular subject, topic, or component is part of a defined curriculum or course of study.
-
C.
subjectType
Indicates the classification or category that defines what kind of entity the subject is.
-
D.
includes
Indicates that one entity contains, encompasses, or has another entity as a part, member, or subset.
-
E.
hasSubjectOfStudy
Indicates that an entity (such as a person or organization) focuses on, researches, or specializes in a particular field or topic of study.
- 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_69c0083082288190b7478cead6b5430a |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0255dc35c8190ab9ee5d269ce553a |
completed | March 22, 2026, 5:22 p.m. |
| PD | Predicate disambiguation | batch_69c021c8195481909419808b002628aa |
completed | March 22, 2026, 5:07 p.m. |
Created at: March 22, 2026, 3:48 p.m.