Triple
T154670
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lisbon |
E3151
|
entity |
| Predicate | hasDistrict |
P459
|
FINISHED |
| Object |
Baixa
Baixa is Lisbon’s historic downtown district, known for its grid-planned streets, grand plazas, and Pombaline architecture rebuilt after the 1755 earthquake.
|
E20143
|
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: Baixa | Statement: [Lisbon, hasDistrict, Baixa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Baixa Context triple: [Lisbon, hasDistrict, Baixa]
-
A.
Barra
Barra is a scenic island in the Outer Hebrides of Scotland, known for its rugged coastline, Gaelic culture, and the unique beach runway at Barra Airport.
-
B.
Barra
Barra is the surname of Mary Barra, the prominent American business executive and CEO of General Motors.
-
C.
Colma
Colma is a small town in San Mateo County, California, best known for its numerous cemeteries and nickname as the "City of Souls."
-
D.
Lower Cape
Lower Cape is the outer portion of Cape Cod in Massachusetts, known for its scenic beaches, dunes, and historic coastal towns.
-
E.
Beacon
Beacon is a small Hudson River city in New York State known for its vibrant arts scene, historic industrial roots, and the contemporary art museum Dia Beacon.
- 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: Baixa Triple: [Lisbon, hasDistrict, Baixa]
Generated description
Baixa is Lisbon’s historic downtown district, known for its grid-planned streets, grand plazas, and Pombaline architecture rebuilt after the 1755 earthquake.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Baixa Target entity description: Baixa is Lisbon’s historic downtown district, known for its grid-planned streets, grand plazas, and Pombaline architecture rebuilt after the 1755 earthquake.
-
A.
Barra
Barra is a scenic island in the Outer Hebrides of Scotland, known for its rugged coastline, Gaelic culture, and the unique beach runway at Barra Airport.
-
B.
Barra
Barra is the surname of Mary Barra, the prominent American business executive and CEO of General Motors.
-
C.
Colma
Colma is a small town in San Mateo County, California, best known for its numerous cemeteries and nickname as the "City of Souls."
-
D.
Lower Cape
Lower Cape is the outer portion of Cape Cod in Massachusetts, known for its scenic beaches, dunes, and historic coastal towns.
-
E.
Beacon
Beacon is a small Hudson River city in New York State known for its vibrant arts scene, historic industrial roots, and the contemporary art museum Dia Beacon.
- 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_69a2527757ec819090b8becb2cf1a862 |
completed | Feb. 28, 2026, 2:27 a.m. |
| NER | Named-entity recognition | batch_69a2582d25448190931c2d785e678a8a |
completed | Feb. 28, 2026, 2:51 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a2d732c32881909640c1c7be70e09a |
completed | Feb. 28, 2026, 11:53 a.m. |
| NEDg | Description generation | batch_69a2d81b278081909d1c4e152cd2ef2c |
completed | Feb. 28, 2026, 11:57 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a2d907b3fc8190bb63024feab379f1 |
completed | Feb. 28, 2026, 12:01 p.m. |
Created at: Feb. 28, 2026, 2:31 a.m.