Triple
T17622295
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | IBRA Version 7 |
E429735
|
entity |
| Predicate | typeOfRegionalization |
P128316
|
FINISHED |
| Object | ecoregional framework |
—
|
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: ecoregional framework | Statement: [IBRA Version 7, typeOfRegionalization, ecoregional framework]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfRegionalization Context triple: [IBRA Version 7, typeOfRegionalization, ecoregional framework]
-
A.
regionType
Indicates the classification or category of a region, specifying what kind of region it is (e.g., administrative, geographic, or functional).
-
B.
regionTypeOfPlace
Indicates that a place belongs to or is categorized under a specific type of geographic or administrative region.
-
C.
politicalRegionType
Indicates the classification of a political region according to its governmental or administrative type (e.g., state, province, municipality).
-
D.
populationRegionType
Indicates the type or category of region (e.g., city, state, country) to which a given population value or statistic applies.
-
E.
regionalGrouping
Indicates that entities are organized or associated together based on shared geographic or regional characteristics.
- 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_69d889e37f308190a6aa0a69daff86c7 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e46db98c54819088dadec9f6bcc559 |
completed | April 19, 2026, 5:52 a.m. |
| PD | Predicate disambiguation | batch_69e3cdd7da34819099bc9481c5a79bab |
completed | April 18, 2026, 6:30 p.m. |
| PDg | Predicate description generation | batch_69e3cfaac2b881909e1140339eb1a0dd |
completed | April 18, 2026, 6:38 p.m. |
Created at: April 10, 2026, 5:52 a.m.