Triple
T5815244
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lisbon District |
E128968
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Oeiras |
E526837
|
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: Oeiras | Statement: [Lisbon District, contains, Oeiras]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Oeiras Context triple: [Lisbon District, contains, Oeiras]
-
A.
Oeiras
chosen
Oeiras is a coastal municipality in the Lisbon metropolitan area of Portugal, known for its residential suburbs, business parks, and proximity to the capital.
-
B.
Barreiro
Barreiro is a small village located on the Cape Verdean island of Maio.
-
C.
Barreiro
Barreiro is a Portuguese city located on the south bank of the Tagus River opposite Lisbon, known historically for its industrial activity and as a commuter hub for the capital.
-
D.
Seixas
Seixas is a surname most notably associated with individuals of Portuguese and Sephardic Jewish heritage.
-
E.
Estoril
Estoril is a coastal resort town in the municipality of Cascais, Portugal, known for its beaches, casino, and historic role as a refuge for exiled royalty and political figures.
- 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_69c0084788848190bcf71f6bc5d71597 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0336344148190bcf417c0b9617cb9 |
completed | March 22, 2026, 6:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c2438c65988190aedb03bed25f19e1 |
completed | March 24, 2026, 7:55 a.m. |
Created at: March 22, 2026, 3:53 p.m.