Triple
T22163597
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sex and Lucia |
E547731
|
entity |
| Predicate | hasCharacter |
P2308
|
FINISHED |
| Object | Belén |
—
|
NE NERFINISHED |
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: Belén | Statement: [Sex and Lucia, hasCharacter, Belén]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Belén Context triple: [Sex and Lucia, hasCharacter, 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
chosen
Belén is a common Spanish feminine given name, often used as a diminutive of "Belén María" and associated with the Spanish word for Bethlehem.
-
C.
Belén
Belén is a small but economically important city in Costa Rica’s Central Valley, known for its industrial parks, business centers, and proximity to the capital, San José.
-
D.
Belén
Belén is a town in northwestern Argentina known for its traditional weaving and role as a regional center in Catamarca Province.
-
E.
Belen
Belen is a small city in central New Mexico known as a regional transportation hub and bedroom community for the Albuquerque metropolitan area.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e11e3c4c5c81908d336165816b12e0 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f12a2f2f90819080b5bb73a6052c24 |
completed | April 28, 2026, 9:44 p.m. |
Created at: April 16, 2026, 8:34 p.m.