Triple
T17615893
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Belén Rueda |
E429081
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Belén
Belén is a common Spanish feminine given name, often used as a diminutive of "Belén María" and associated with the Spanish word for Bethlehem.
|
E1277914
|
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: Belén | Statement: [Belén Rueda, givenName, Belén]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Belén Context triple: [Belén Rueda, givenName, Belén]
-
A.
Belén
Belén is a municipality located in the Rivas Department of southwestern Nicaragua, known for its rural character and agricultural activities.
-
B.
Belén
Belén is a town in northwestern Argentina known for its traditional weaving and role as a regional center in Catamarca Province.
-
C.
Belen
Belen is a small city in central New Mexico known as a regional transportation hub and bedroom community for the Albuquerque metropolitan area.
-
D.
Natividad
Natividad is a landlocked agricultural municipality in the province of Pangasinan in the Philippines, known for its rural landscapes and eco-tourism sites.
-
E.
Natividad
Natividad is a barangay (village-level administrative division) located in the municipality of San Narciso in the province of Zambales, Philippines.
- 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: Belén Triple: [Belén Rueda, givenName, Belén]
Generated description
Belén is a common Spanish feminine given name, often used as a diminutive of "Belén María" and associated with the Spanish word for Bethlehem.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Belén Target entity description: Belén is a common Spanish feminine given name, often used as a diminutive of "Belén María" and associated with the Spanish word for Bethlehem.
-
A.
Belén
Belén is a town in northwestern Argentina known for its traditional weaving and role as a regional center in Catamarca Province.
-
B.
Belén
Belén is a municipality located in the Rivas Department of southwestern Nicaragua, known for its rural character and agricultural activities.
-
C.
Belen
Belen is a small city in central New Mexico known as a regional transportation hub and bedroom community for the Albuquerque metropolitan area.
-
D.
Natividad
Natividad is a landlocked agricultural municipality in the province of Pangasinan in the Philippines, known for its rural landscapes and eco-tourism sites.
-
E.
Natividad
Natividad is a barangay (village-level administrative division) located in the municipality of San Narciso in the province of Zambales, Philippines.
- 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_69d889e1c6148190ba76241e74688f8b |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e46d32991c81909801161b0a416c94 |
completed | April 19, 2026, 5:50 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a01e82849748190a6ce3a1f7a7fc77b |
completed | May 11, 2026, 2:31 p.m. |
| NEDg | Description generation | batch_6a01ecfb2ff4819082f67ab1f2ce8885 |
completed | May 11, 2026, 2:51 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a01ee0c03e881908aaaa3bd0f596387 |
completed | May 11, 2026, 2:56 p.m. |
Created at: April 10, 2026, 5:51 a.m.