Triple
T1818349
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | IR64 |
E40486
|
entity |
| Predicate | hasGrainQuality |
P32632
|
FINISHED |
| Object | good grain quality |
—
|
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: good grain quality | Statement: [IR64, hasGrainQuality, good grain quality]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGrainQuality Context triple: [IR64, hasGrainQuality, good grain quality]
-
A.
grain
Indicates that one entity is composed of or contains a granular substance or small particles of another entity.
-
B.
fieldQuality
Indicates the assessed level or degree of quality associated with a particular field or attribute in a given context.
-
C.
storageQuality
Indicates the degree or standard of how well something is stored, such as its preservation, safety, or suitability for use.
-
D.
grainSize
Indicates the relative coarseness or fineness of the material or particles involved in the relationship.
-
E.
typeOfFarmProductInDispute
Indicates that a specific kind of farm product is the subject of a disagreement, conflict, or legal dispute between parties.
- 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_69a8864526c081908a3a4d74f689e2c5 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69aba67721788190951beae25e885457 |
completed | March 7, 2026, 4:15 a.m. |
| PD | Predicate disambiguation | batch_69aa61d884548190a19cf3a6b5ae9d48 |
completed | March 6, 2026, 5:10 a.m. |
| PDg | Predicate description generation | batch_69aba67554788190b429f2b9f0a70310 |
completed | March 7, 2026, 4:15 a.m. |
Created at: March 4, 2026, 7:32 p.m.