Triple
T13201617
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chamartín |
E314254
|
entity |
| Predicate | borderedBy |
P224
|
FINISHED |
| Object | Salamanca |
E55297
|
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: Salamanca | Statement: [Chamartín, borderedBy, Salamanca]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Salamanca Context triple: [Chamartín, borderedBy, Salamanca]
-
A.
Salamanca
chosen
Salamanca is a historic city in western Spain renowned for its ancient university, golden sandstone architecture, and well-preserved medieval old town.
-
B.
Salamanca
Salamanca is an industrial city in central Mexico known for its major oil refinery and role in the country's petrochemical sector.
-
C.
Salamanca
Salamanca is a Chilean town and municipality in the Coquimbo Region, known for its agricultural production and location in the Choapa Valley.
-
D.
Alcalá de Henares
Alcalá de Henares is a historic Spanish city east of Madrid, renowned as the birthplace of Miguel de Cervantes and for its well-preserved university and medieval architecture.
-
E.
Alcalá la Real
Alcalá la Real is a historic town in southern Spain known for its imposing La Mota fortress and strategic location between Granada and Jaén.
- 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_69d806aee7308190b70a237ba2a6e3e1 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98c6591d881909a6ebc22246caead |
completed | April 10, 2026, 11:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6ff1a3d68819089ad35f8f9ff5c5a |
completed | May 3, 2026, 7:54 a.m. |
Created at: April 9, 2026, 9:16 p.m.