Triple
T16060229
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Riba-roja d’Ebre |
E389587
|
entity |
| Predicate | hasCadastralClassification |
P25488
|
FINISHED |
| Object | municipal territory |
—
|
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: municipal territory | Statement: [Riba-roja d’Ebre, hasCadastralClassification, municipal territory]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCadastralClassification Context triple: [Riba-roja d’Ebre, hasCadastralClassification, municipal territory]
-
A.
hasCadastralArea
Indicates that an entity possesses or is associated with a specific cadastral (official land registry) area measurement.
-
B.
cadastralUnitOf
Indicates that one entity is a cadastral unit (a legally defined land parcel or property unit) that belongs to or is part of another, typically larger, administrative or land-management entity.
-
C.
hasUrbanClassification
Indicates that an entity is assigned a specific urban status or category within a defined classification system.
-
D.
hasLCClassification
Indicates that an entity is assigned a specific Library of Congress Classification code representing its subject or shelving category.
-
E.
areClassifiedBy
chosen
Indicates that entities are assigned to one or more categories, types, or classes according to a specified classification scheme.
- 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_69d86dae698881908327ef2d67706cb9 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e1858a00888190b8505071575dc56f |
completed | April 17, 2026, 12:57 a.m. |
| PD | Predicate disambiguation | batch_69e18272f2288190a17d45fb01cc2b07 |
completed | April 17, 2026, 12:44 a.m. |
Created at: April 10, 2026, 4:57 a.m.