Triple
T4690542
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beijing Declaration and Platform for Action |
E104023
|
entity |
| Predicate | numberOfCriticalAreasOfConcern |
P31088
|
FINISHED |
| Object | 12 |
—
|
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: 12 | Statement: [Beijing Declaration and Platform for Action, numberOfCriticalAreasOfConcern, 12]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfCriticalAreasOfConcern Context triple: [Beijing Declaration and Platform for Action, numberOfCriticalAreasOfConcern, 12]
-
A.
keyIssueArea
Indicates that something is a primary topic, domain, or field that is central or especially important within a broader context or discussion.
-
B.
numberOfIssues
chosen
Indicates the quantity of issues associated with a given entity or context.
-
C.
hasCriticalConcept
Indicates that one entity includes, depends on, or is defined by a key concept that is essential to understanding or functioning of another entity.
-
D.
numberOfAreaBoards
Indicates the total count of area boards associated with or defined for a given entity or context.
-
E.
numberOfIndicators
Indicates the total count of indicators associated with or relevant to a given entity or context.
- 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_69bd43df91f481908e9add1b617b60ef |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd66059bfc8190885d26d05dd38df1 |
completed | March 20, 2026, 3:21 p.m. |
| PD | Predicate disambiguation | batch_69bd6219da948190bbbb50f08573ab4d |
completed | March 20, 2026, 3:04 p.m. |
Created at: March 20, 2026, 1:16 p.m.