Triple
T5739425
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Combined Defence Services Examination |
E126576
|
entity |
| Predicate | includesSubjects |
P24066
|
FINISHED |
| Object | English |
—
|
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: English | Statement: [Combined Defence Services Examination, includesSubjects, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: includesSubjects Context triple: [Combined Defence Services Examination, includesSubjects, English]
-
A.
includesTopics
chosen
Indicates that one entity contains, covers, or addresses the specified topics as part of its content or scope.
-
B.
isSubjectTo
Indicates that one entity is governed, affected, or constrained by the authority, rules, conditions, or influence of another entity.
-
C.
includedWith
Indicates that one entity is provided or packaged together as part of another entity.
-
D.
includesSee
Indicates that one entity’s scope, content, or experience contains or encompasses the act of seeing or visual perception involving another entity.
-
E.
requiresSubjectsAtLevel
Indicates that an entity depends on other subjects being present or qualified at a specified level in order for a condition, action, or state to be valid or achievable.
- 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.