Triple
T8973795
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Food Grains of India |
E214332
|
entity |
| Predicate | timeOfStudy |
P49391
|
FINISHED |
| Object | 19th-century Indian agriculture |
—
|
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: 19th-century Indian agriculture | Statement: [Food Grains of India, timeOfStudy, 19th-century Indian agriculture]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: timeOfStudy Context triple: [Food Grains of India, timeOfStudy, 19th-century Indian agriculture]
-
A.
studiesFor
Indicates that one entity engages in studying or academic preparation with the purpose of achieving or supporting another entity (such as a goal, exam, or qualification).
-
B.
primaryDurationOfStudy
chosen
Indicates the main length of time allocated or required for a particular course of study or educational program.
-
C.
modernDisciplineStudying
Indicates that a contemporary academic or scientific discipline is engaged in the systematic study or investigation of a given subject or phenomenon.
-
D.
partOfStudy
Indicates that something is a component, segment, or subset within a larger study or research project.
-
E.
stateStudied
Indicates that a person has studied or received education in a particular state.
- 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_69ca839dbf608190a2f5990477115d29 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc6783abe48190840e652fc2acf28f |
completed | April 1, 2026, 12:32 a.m. |
| PD | Predicate disambiguation | batch_69cc5ed9a2d48190ad11381078e823b7 |
completed | March 31, 2026, 11:55 p.m. |
Created at: March 30, 2026, 7:02 p.m.