Triple
T17124878
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beira Interior |
E415565
|
entity |
| Predicate | containsTown |
P847
|
FINISHED |
| Object | Sertã |
E375176
|
NE 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: Sertã | Statement: [Beira Interior, containsTown, Sertã]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sertã Context triple: [Beira Interior, containsTown, Sertã]
-
A.
Sertã
chosen
Sertã is a municipality and town in central Portugal known for its forested landscapes, river beaches, and traditional cuisine.
-
B.
Ribeira Brava
Ribeira Brava is the main town and administrative center of the island of São Nicolau in Cape Verde, known for its coastal setting and colonial-era architecture.
-
C.
Cordinhã
Cordinhã is a civil parish located in the municipality of Cantanhede in the Coimbra District of central Portugal.
-
D.
Barrocal Algarvio
Barrocal Algarvio is a transitional inland region of Portugal’s Algarve known for its rolling hills, traditional villages, and mixed agricultural landscapes between the coastal strip and the mountainous interior.
-
E.
Sernancelhe
Sernancelhe is a municipality in northern Portugal known for its historic granite architecture, religious heritage, and scenic rural landscapes.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d886d090cc8190a39cb94992586905 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3f025fce481908e261f2e363e14f9 |
completed | April 18, 2026, 8:57 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a013a12a7288190911c1be2667916c0 |
completed | May 11, 2026, 2:08 a.m. |
Created at: April 10, 2026, 5:36 a.m.