Triple
T31002862
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Count of Leuven |
E789985
|
entity |
| Predicate | modernRegionEquivalent |
P25757
|
FINISHED |
| Object | Flemish Brabant |
—
|
NE NERFINISHED |
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: Flemish Brabant | Statement: [Count of Leuven, modernRegionEquivalent, Flemish Brabant]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: modernRegionEquivalent Context triple: [Count of Leuven, modernRegionEquivalent, Flemish Brabant]
-
A.
modernRegion
chosen
Indicates that an entity is located within or associated with a contemporary, present-day geographic or administrative region.
-
B.
modernUsageRegion
Indicates the geographic region where something is currently or most commonly used in modern times.
-
C.
modernNameOfArea
Indicates that one area entity represents the current or modern name of another area entity.
-
D.
exportRegion
Indicates the region or geographic area from which goods, services, or resources are exported.
-
E.
historicalRegionCode
Indicates that an entity is associated with a specific code identifying a historical region.
- 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_69f224c65a348190baaed1c01a29900c |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f7b2f3a104819098ddd8909eaf596c |
completed | May 3, 2026, 8:41 p.m. |
| PD | Predicate disambiguation | batch_69f7b1b8a9fc8190a1279e67a2d12707 |
completed | May 3, 2026, 8:36 p.m. |
Created at: April 29, 2026, 8:57 p.m.