Triple
T9732065
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aveiro |
E235768
|
entity |
| Predicate | belongsToNUTS2Region |
P9956
|
FINISHED |
| Object |
Centro
Centro is a NUTS 2 statistical region in central Portugal that includes areas such as Aveiro and Coimbra.
|
E816316
|
NE FINISHED |
How this triple was built (4 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: Centro | Statement: [Aveiro, belongsToNUTS2Region, Centro]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Centro Context triple: [Aveiro, belongsToNUTS2Region, Centro]
-
A.
Centro Sur
Centro Sur is a province in mainland Equatorial Guinea, known for its inland location and administrative role within the Río Muni region.
-
B.
Riocentro
Riocentro is a major convention and exhibition center in Rio de Janeiro, Brazil, known for hosting large-scale events such as international conferences, trade shows, and sports competitions.
-
C.
Diré
Diré is a town in northern Mali situated along the Niger River, known as a local commercial and cultural center where the Koyra Chiini language is widely spoken.
-
D.
Baarìa
Baarìa is an Italian epic drama film directed by Giuseppe Tornatore that chronicles several generations of life, politics, and love in a Sicilian town.
-
E.
Belén
Belén is a town in northwestern Argentina known for its traditional weaving and role as a regional center in Catamarca Province.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Centro Triple: [Aveiro, belongsToNUTS2Region, Centro]
Generated description
Centro is a NUTS 2 statistical region in central Portugal that includes areas such as Aveiro and Coimbra.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Centro Target entity description: Centro is a NUTS 2 statistical region in central Portugal that includes areas such as Aveiro and Coimbra.
-
A.
Centro Sur
Centro Sur is a province in mainland Equatorial Guinea, known for its inland location and administrative role within the Río Muni region.
-
B.
Riocentro
Riocentro is a major convention and exhibition center in Rio de Janeiro, Brazil, known for hosting large-scale events such as international conferences, trade shows, and sports competitions.
-
C.
Diré
Diré is a town in northern Mali situated along the Niger River, known as a local commercial and cultural center where the Koyra Chiini language is widely spoken.
-
D.
Baarìa
Baarìa is an Italian epic drama film directed by Giuseppe Tornatore that chronicles several generations of life, politics, and love in a Sicilian town.
-
E.
Belén
Belén is a town in northwestern Argentina known for its traditional weaving and role as a regional center in Catamarca Province.
- F. None of above. chosen
Provenance (5 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_69ca84d0fad481909cdd45aa77416c48 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cd9eb3d6e4819090b3c7fb92550c57 |
completed | April 1, 2026, 10:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d19fbbba2081909a15725a68423162 |
completed | April 4, 2026, 11:33 p.m. |
| NEDg | Description generation | batch_69d1a065ce008190985b792302daa7cb |
completed | April 4, 2026, 11:36 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d1a0f811fc8190b6a46a0441159089 |
completed | April 4, 2026, 11:38 p.m. |
Created at: March 30, 2026, 8:22 p.m.