Triple
T6347910
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ASEAN Socio-Cultural Community Blueprint 2025 |
E142790
|
entity |
| Predicate | coversPillar |
P61123
|
FINISHED |
| Object | human development |
—
|
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: human development | Statement: [ASEAN Socio-Cultural Community Blueprint 2025, coversPillar, human development]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: coversPillar Context triple: [ASEAN Socio-Cultural Community Blueprint 2025, coversPillar, human development]
-
A.
coversSection
Indicates that one entity includes, addresses, or provides content for a particular section of another entity.
-
B.
coversLevel
Indicates that one entity includes or encompasses a particular level or layer of another entity or system.
-
C.
coversField
Indicates that one entity extends over, protects, or occupies the surface or area of a field associated with another entity.
-
D.
alsoCovers
Indicates that something extends its scope or applicability to include an additional subject, area, or case beyond what was originally covered.
-
E.
coversAspect
chosen
Indicates that one entity addresses, includes, or deals with a particular aspect or facet of another entity or topic.
- 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_69c008d6dcbc8190aa1c2f1fd8916b42 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c067ba2c64819094fa38bb2aeffa6c |
completed | March 22, 2026, 10:05 p.m. |
| PD | Predicate disambiguation | batch_69c060ea1a988190889e47b7e0c819b8 |
completed | March 22, 2026, 9:36 p.m. |
Created at: March 22, 2026, 4:31 p.m.