Triple
T2073237
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mê Linh District |
E44862
|
entity |
| Predicate | hasRuralCommunes |
P34764
|
FINISHED |
| Object | communes of Mê Linh District |
—
|
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: communes of Mê Linh District | Statement: [Mê Linh District, hasRuralCommunes, communes of Mê Linh District]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRuralCommunes Context triple: [Mê Linh District, hasRuralCommunes, communes of Mê Linh District]
-
A.
hasRuralArea
Indicates that an entity includes, is associated with, or contains a countryside or sparsely populated geographic area.
-
B.
hasNumberOfMunicipalities
Indicates the relationship that specifies how many municipalities are associated with or contained within a given administrative or geographic entity.
-
C.
isRural
Indicates that something is located in, characteristic of, or associated with a countryside or non-urban area.
-
D.
isRuralCounty
Indicates that a given county is classified as rural rather than urban based on demographic, geographic, or administrative criteria.
-
E.
hasSuburbanAreas
Indicates that a place includes or is associated with surrounding residential suburban districts or neighborhoods.
- 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_69a88916c2b48190a5ca2e9b12cad3ed |
completed | March 4, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69abba101c008190840763d2f28fa8d7 |
completed | March 7, 2026, 5:39 a.m. |
| PD | Predicate disambiguation | batch_69abb7b0edac8190a58eabee55f73deb |
completed | March 7, 2026, 5:29 a.m. |
| PDg | Predicate description generation | batch_69abb85fe7a08190b991b1f23bc34f93 |
completed | March 7, 2026, 5:32 a.m. |
Created at: March 4, 2026, 7:41 p.m.