Triple
T132500
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Food and Agriculture Organization |
E2681
|
entity |
| Predicate | typeOfProgram |
P2192
|
FINISHED |
| Object | technical assistance |
—
|
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: technical assistance | Statement: [Food and Agriculture Organization, typeOfProgram, technical assistance]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfProgram Context triple: [Food and Agriculture Organization, typeOfProgram, technical assistance]
-
A.
programType
chosen
Indicates the category or kind of program to which an entity belongs or with which it is associated.
-
B.
program
Indicates that an entity creates, writes, or develops a computer program or software application.
-
C.
codeType
Indicates the classification or category assigned to a particular code within a coding or encoding system.
-
D.
programmingLanguage
Indicates that one entity is a programming language used to create, control, or interact with the other entity.
-
E.
scriptType
Indicates the classification or category of a script, specifying what kind of script it is (e.g., its format, purpose, or scripting language type).
- 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_69a2520c0f3481908b0ed054a2fca8d0 |
completed | Feb. 28, 2026, 2:25 a.m. |
| NER | Named-entity recognition | batch_69a25855baf48190a1b63f2e5865d957 |
completed | Feb. 28, 2026, 2:52 a.m. |
| PD | Predicate disambiguation | batch_69a2564edb488190974dc00eb9ac37d9 |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:30 a.m.