Triple
T11316859
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arecibo, Puerto Rico |
E267989
|
entity |
| Predicate | hasBarrio |
P4813
|
FINISHED |
| Object |
Miraflores
Miraflores is a rural barrio (district) of the municipality of Arecibo in northern Puerto Rico.
|
E918797
|
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: Miraflores | Statement: [Arecibo, Puerto Rico, hasBarrio, Miraflores]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Miraflores Context triple: [Arecibo, Puerto Rico, hasBarrio, Miraflores]
-
A.
Miraflores
Miraflores is an upscale coastal district of Lima, Peru, known for its shopping, dining, nightlife, and cliffside views over the Pacific Ocean.
-
B.
San Juan de Miraflores
San Juan de Miraflores is a populous residential district in southern Lima, Peru, known for its working-class neighborhoods and rapid urban growth.
-
C.
Surquillo
Surquillo is a densely populated urban district of Lima, Peru, known for its residential neighborhoods, markets, and proximity to the upscale area of Miraflores.
-
D.
Callao
Callao is Peru’s chief seaport and a major coastal city adjacent to Lima, serving as the country’s principal gateway for maritime trade.
-
E.
Callao
Callao is a central Madrid Metro station located in the busy commercial and entertainment hub around Plaza del Callao in the city center.
- 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: Miraflores Triple: [Arecibo, Puerto Rico, hasBarrio, Miraflores]
Generated description
Miraflores is a rural barrio (district) of the municipality of Arecibo in northern Puerto Rico.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Miraflores Target entity description: Miraflores is a rural barrio (district) of the municipality of Arecibo in northern Puerto Rico.
-
A.
Miraflores
Miraflores is an upscale coastal district of Lima, Peru, known for its shopping, dining, nightlife, and cliffside views over the Pacific Ocean.
-
B.
San Juan de Miraflores
San Juan de Miraflores is a populous residential district in southern Lima, Peru, known for its working-class neighborhoods and rapid urban growth.
-
C.
Surquillo
Surquillo is a densely populated urban district of Lima, Peru, known for its residential neighborhoods, markets, and proximity to the upscale area of Miraflores.
-
D.
Callao
Callao is Peru’s chief seaport and a major coastal city adjacent to Lima, serving as the country’s principal gateway for maritime trade.
-
E.
Callao
Callao is a central Madrid Metro station located in the busy commercial and entertainment hub around Plaza del Callao in the city center.
- 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_69d6aaca5c24819083db46a30d86cb34 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e9c3cf748190987838029d9f7fff |
completed | April 9, 2026, 6:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e525c35538819085d76f7cdf362316 |
completed | April 19, 2026, 6:58 p.m. |
| NEDg | Description generation | batch_69e52c81449c8190847b64fa91a45b2e |
completed | April 19, 2026, 7:26 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69e531b079708190ac9e19127d36a848 |
completed | April 19, 2026, 7:49 p.m. |
Created at: April 8, 2026, 9:32 p.m.