Triple
T6650608
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Western Catalonia |
E150809
|
entity |
| Predicate | hasMajorCity |
P316
|
FINISHED |
| Object | Cervera |
E97309
|
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: Cervera | Statement: [Western Catalonia, hasMajorCity, Cervera]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cervera Context triple: [Western Catalonia, hasMajorCity, Cervera]
-
A.
Cervera
chosen
Cervera is a Spanish surname historically associated with notable figures such as Admiral Pascual Cervera y Topete.
-
B.
Spínola
Spínola is a Portuguese surname most prominently associated with António de Spínola, a key military figure and political leader during Portugal’s Carnation Revolution.
-
C.
Azaña
Azaña is the surname of Manuel Azaña, a prominent Spanish politician and writer who served as President of the Second Spanish Republic.
-
D.
Rivas
Rivas is a city in southwestern Nicaragua known as a regional commercial center and gateway between Lake Nicaragua and the Pacific coast.
-
E.
La Serna
La Serna is a station on Madrid Metro’s Line C-5 commuter rail corridor serving the Fuenlabrada area in the Community of Madrid, Spain.
- 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_69c687f2c9508190a60b9aad31d3f358 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6b04408508190a87a669b32364368 |
completed | March 27, 2026, 4:28 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6eefb3b6c8190ba797dc51966e3a5 |
completed | March 27, 2026, 8:56 p.m. |
Created at: March 27, 2026, 2:01 p.m.