Triple
T16060504
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Baix Camp |
E389596
|
entity |
| Predicate | containsMunicipality |
P852
|
FINISHED |
| Object |
Duesaigües
Duesaigües is a small municipality in the Baix Camp comarca of Catalonia, Spain, known for its scenic mountainous surroundings and rural character.
|
E1191101
|
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: Duesaigües | Statement: [Baix Camp, containsMunicipality, Duesaigües]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Duesaigües Context triple: [Baix Camp, containsMunicipality, Duesaigües]
-
A.
Matalascañas
Matalascañas is a popular seaside resort town in southern Spain known for its long sandy beaches and proximity to Doñana National Park.
-
B.
Comasch
Comasch is an alternative name for the Comasco dialect, a regional variety of the Lombard language spoken around the city of Como in northern Italy.
-
C.
Royuela
Royuela is a small rural municipality in the province of Teruel, Aragon, Spain, known for its scenic natural surroundings and traditional village character.
-
D.
Maragall
Maragall is a Barcelona Metro station that serves as an interchange point between multiple lines in the city’s public transit network.
-
E.
Échevis
Échevis is a small commune in southeastern France, located in the Drôme department within the Auvergne-Rhône-Alpes region.
- 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: Duesaigües Triple: [Baix Camp, containsMunicipality, Duesaigües]
Generated description
Duesaigües is a small municipality in the Baix Camp comarca of Catalonia, Spain, known for its scenic mountainous surroundings and rural character.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Duesaigües Target entity description: Duesaigües is a small municipality in the Baix Camp comarca of Catalonia, Spain, known for its scenic mountainous surroundings and rural character.
-
A.
Matalascañas
Matalascañas is a popular seaside resort town in southern Spain known for its long sandy beaches and proximity to Doñana National Park.
-
B.
Comasch
Comasch is an alternative name for the Comasco dialect, a regional variety of the Lombard language spoken around the city of Como in northern Italy.
-
C.
Royuela
Royuela is a small rural municipality in the province of Teruel, Aragon, Spain, known for its scenic natural surroundings and traditional village character.
-
D.
Maragall
Maragall is a Barcelona Metro station that serves as an interchange point between multiple lines in the city’s public transit network.
-
E.
Échevis
Échevis is a small commune in southeastern France, located in the Drôme department within the Auvergne-Rhône-Alpes region.
- 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_69d86dae698881908327ef2d67706cb9 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e1837850288190910ef37d6484c600 |
completed | April 17, 2026, 12:48 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffdbe88a608190bc0a0cbfdb71e81d |
completed | May 10, 2026, 1:14 a.m. |
| NEDg | Description generation | batch_69ffdce9591c81909e6bb5c13ddf84cd |
completed | May 10, 2026, 1:18 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ffddb0ff848190ace70b55d9861040 |
completed | May 10, 2026, 1:21 a.m. |
Created at: April 10, 2026, 4:57 a.m.