Triple
T5394699
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sustainable Development Goal 11 |
E120622
|
entity |
| Predicate | target11.3Focus |
P31
|
FINISHED |
| Object | inclusive and sustainable urbanization |
—
|
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: inclusive and sustainable urbanization | Statement: [Sustainable Development Goal 11, target11.3Focus, inclusive and sustainable urbanization]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: target11.3Focus Context triple: [Sustainable Development Goal 11, target11.3Focus, inclusive and sustainable urbanization]
-
A.
target
Indicates that one entity is the intended object, goal, or focus of another entity’s action or attention.
-
B.
focusesOn
chosen
Indicates that one entity directs its attention, effort, or primary activity toward another entity or specific subject.
-
C.
primaryTarget
Indicates that an entity is the main or most important target of another entity’s action, focus, or effect.
-
D.
targetWork
Indicates that one entity is the specific work (e.g., document, artwork, or project) that another entity is directed at, refers to, or is primarily concerned with.
-
E.
targetsUseCase
Indicates that one entity is aimed at or designed to address a particular use case associated with another entity.
- 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_69bd4637b92c8190b815b6443ae4b323 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd87441a208190b79561614759894b |
completed | March 20, 2026, 5:43 p.m. |
| PD | Predicate disambiguation | batch_69bd8463a9c88190bd760378f3026180 |
completed | March 20, 2026, 5:31 p.m. |
Created at: March 20, 2026, 2:04 p.m.