Triple
T34227181
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Avià |
E878084
|
entity |
| Predicate | hasCapitalOfComarcaNearby |
P124642
|
FINISHED |
| Object | Berga |
—
|
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: Berga | Statement: [Avià, hasCapitalOfComarcaNearby, Berga]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCapitalOfComarcaNearby Context triple: [Avià, hasCapitalOfComarcaNearby, Berga]
-
A.
hasComarcaCapitalRole
chosen
Indicates that an entity serves as the capital or administrative center (comarca capital) for a given territorial or jurisdictional unit.
-
B.
hasMunicipalitySeatNearby
Indicates that the municipality’s administrative seat is located in close proximity to the referenced place or entity.
-
C.
hasComarca
Indicates that one entity is associated with, or belongs to, a specific comarca (an administrative or territorial district).
-
D.
countyCapitalNearby
Indicates that a county’s capital city is located close to a specified place or entity.
-
E.
hasDepartmentCapitalNearby
Indicates that the subject entity has a departmental capital city located in close geographical proximity to it.
- 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_69f349b16d0481908754e3069f05e0c1 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69ff5b233e9c8190adc06cca0758986b |
completed | May 9, 2026, 4:04 p.m. |
| PD | Predicate disambiguation | batch_69ff5a5682108190a006b23c4fcdcc7c |
completed | May 9, 2026, 4:01 p.m. |
Created at: May 1, 2026, 1:56 a.m.