Triple
T14006789
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beira Corridor |
E336969
|
entity |
| Predicate | terminusAt |
P388
|
FINISHED |
| Object | Beira |
E66877
|
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: Beira | Statement: [Beira Corridor, terminusAt, Beira]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Beira Context triple: [Beira Corridor, terminusAt, Beira]
-
A.
Beira
chosen
Beira is a major port city in central Mozambique, serving as a key commercial and transport hub for the region.
-
B.
Beira (Portugal)
Beira is a historical region in central Portugal known for its mountainous landscapes, fortified towns, and role as a traditional territorial division of the country.
-
C.
Lourenço Marques
Lourenço Marques is the former name of Maputo, the capital city and main port of Mozambique.
-
D.
Cantanhede
Cantanhede is a Portuguese municipality in the Centro Region known for its wine production, agricultural activity, and proximity to the Atlantic coast.
-
E.
Beira Alta
Beira Alta is a historical province in north-central Portugal known for its mountainous landscapes, fortified towns, and wine-producing regions.
- 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_69d81c645c5c8190b1fd16a285a1b78a |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2ed327d88190a53af5768468a8eb |
completed | April 14, 2026, 12:10 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fbc329891c8190b4dcb9913e235a1c |
completed | May 6, 2026, 10:39 p.m. |
Created at: April 9, 2026, 10:19 p.m.