Triple
T24627355
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ABC Region of Greater São Paulo |
E609577
|
entity |
| Predicate | regionCodeUsedIn |
P156800
|
FINISHED |
| Object | regional planning of São Paulo metropolitan area |
—
|
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: regional planning of São Paulo metropolitan area | Statement: [ABC Region of Greater São Paulo, regionCodeUsedIn, regional planning of São Paulo metropolitan area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: regionCodeUsedIn Context triple: [ABC Region of Greater São Paulo, regionCodeUsedIn, regional planning of São Paulo metropolitan area]
-
A.
regionCodeType
Indicates the classification or format type used for a given region code within a coding or identification system.
-
B.
regionCodeMeaning
Indicates that a region code is associated with its corresponding descriptive meaning or label.
-
C.
regionCodePattern
Indicates the standardized format or pattern that valid region codes must follow.
-
D.
hasRegionCode
Indicates that an entity is associated with a specific regional identifier or code.
-
E.
locationCode
Indicates the specific coded location associated with an entity, event, or relationship.
- 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_69e2c4d1d3708190a0f2dc6a3a8523bb |
completed | April 17, 2026, 11:40 p.m. |
| NER | Named-entity recognition | batch_69f2be044d4c819094e14eda28d371a7 |
completed | April 30, 2026, 2:27 a.m. |
| PD | Predicate disambiguation | batch_69f2a6d0ab708190b2e3b94dd20ca76b |
completed | April 30, 2026, 12:48 a.m. |
| PDg | Predicate description generation | batch_69f2b8b8bc5881908df49c0b07110246 |
completed | April 30, 2026, 2:04 a.m. |
Created at: April 18, 2026, 2:32 a.m.