Triple
T128799
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lima |
E2605
|
entity |
| Predicate | hasDistrict |
P459
|
FINISHED |
| Object |
San Isidro
San Isidro is an upscale, modern district of Lima, Peru, known for its financial center, embassies, parks, and high-end residential areas.
|
E22180
|
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: San Isidro | Statement: [Lima, hasDistrict, San Isidro]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: San Isidro Context triple: [Lima, hasDistrict, San Isidro]
-
A.
San Francisco de Paula
San Francisco de Paula is a suburban district on the outskirts of Havana, Cuba, known for its association with Ernest Hemingway and his former residence, Finca Vigía.
-
B.
Concepción
Concepción is a major Chilean city in the south-central part of the country, known as an important industrial, commercial, and educational center.
-
C.
Concepción
Concepción was one of the ships in Ferdinand Magellan’s expedition that took part in the first circumnavigation of the globe.
-
D.
Santiago de Veraguas
Santiago de Veraguas is a principal urban and commercial center in western Panama and the capital of Veraguas Province.
-
E.
Ciudad Serdán
Ciudad Serdán is a town in the Mexican state of Puebla, known as a gateway community to the nearby Pico de Orizaba volcano and surrounding highland region.
- 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: San Isidro Triple: [Lima, hasDistrict, San Isidro]
Generated description
San Isidro is an upscale, modern district of Lima, Peru, known for its financial center, embassies, parks, and high-end residential areas.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: San Isidro Target entity description: San Isidro is an upscale, modern district of Lima, Peru, known for its financial center, embassies, parks, and high-end residential areas.
-
A.
San Francisco de Paula
San Francisco de Paula is a suburban district on the outskirts of Havana, Cuba, known for its association with Ernest Hemingway and his former residence, Finca Vigía.
-
B.
Concepción
Concepción is a major Chilean city in the south-central part of the country, known as an important industrial, commercial, and educational center.
-
C.
Concepción
Concepción was one of the ships in Ferdinand Magellan’s expedition that took part in the first circumnavigation of the globe.
-
D.
Santiago de Veraguas
Santiago de Veraguas is a principal urban and commercial center in western Panama and the capital of Veraguas Province.
-
E.
Ciudad Serdán
Ciudad Serdán is a town in the Mexican state of Puebla, known as a gateway community to the nearby Pico de Orizaba volcano and surrounding highland region.
- 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_69a2520c0f3481908b0ed054a2fca8d0 |
completed | Feb. 28, 2026, 2:25 a.m. |
| NER | Named-entity recognition | batch_69a2576518e0819096b35d8af7a4d1bd |
completed | Feb. 28, 2026, 2:48 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a2eb76c1b88190a36cfb803dc12af7 |
completed | Feb. 28, 2026, 1:19 p.m. |
| NEDg | Description generation | batch_69a2ec3f38f88190a1314f2cebf1e776 |
completed | Feb. 28, 2026, 1:23 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69a2ecd7e33481908a075cfe532025c0 |
completed | Feb. 28, 2026, 1:25 p.m. |
Created at: Feb. 28, 2026, 2:30 a.m.