Triple
T3820374
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | GRE Subject Tests |
E84356
|
entity |
| Predicate | statusOfLiteratureInEnglishTest |
P52469
|
FINISHED |
| Object | discontinued |
—
|
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: discontinued | Statement: [GRE Subject Tests, statusOfLiteratureInEnglishTest, discontinued]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: statusOfLiteratureInEnglishTest Context triple: [GRE Subject Tests, statusOfLiteratureInEnglishTest, discontinued]
-
A.
inLiterature
Indicates that a work, concept, or entity is mentioned, discussed, or represented within a piece of literature.
-
B.
hasLiteraryStandard
Indicates that one entity defines, specifies, or embodies the accepted literary norm or standard used by another entity.
-
C.
statusInEnglishLaw
Indicates the legal standing, classification, or condition of something as defined within the framework of English law.
-
D.
literarySubject
Indicates that one entity serves as the subject, topic, or focus of a literary work created by another entity.
-
E.
literaryLanguage
Indicates that an entity is expressed, written, or communicated using a particular literary or standardized written language.
- 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_69aed931f5908190be2c07af66d4df25 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aef188b474819087680db42b04ecdd |
completed | March 9, 2026, 4:12 p.m. |
| PD | Predicate disambiguation | batch_69aee74a2bc081909b237df8b1e27653 |
completed | March 9, 2026, 3:29 p.m. |
| PDg | Predicate description generation | batch_69aef18748648190b85e62f7796ff4b4 |
completed | March 9, 2026, 4:12 p.m. |
Created at: March 9, 2026, 3:17 p.m.