Triple
T792969
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | La Molina |
E16954
|
entity |
| Predicate | hasNeighboringDistrict |
P17964
|
FINISHED |
| Object |
San Luis
San Luis is a residential and commercial district located in the eastern part of Lima, Peru.
|
E99053
|
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 Luis | Statement: [La Molina, hasNeighboringDistrict, San Luis]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: San Luis Context triple: [La Molina, hasNeighboringDistrict, San Luis]
-
A.
Santa Fe
Santa Fe is a major modern business and financial district in western Mexico City known for its corporate offices, upscale shopping centers, and contemporary high-rise architecture.
-
B.
San Carlos
San Carlos is a city in San Mateo County, California, located on the San Francisco Peninsula between Belmont and Redwood City.
-
C.
San Carlos
San Carlos is a Nicaraguan town that serves as a key river and lake port near the southeastern end of Lake Nicaragua.
-
D.
Durango
Durango is a state in north-central Mexico known for its rugged mountainous terrain, significant mining history, and role as a setting for classic Western films.
-
E.
Santa Fe, New Mexico
Santa Fe, New Mexico is the capital city of New Mexico, renowned for its Pueblo-style architecture, vibrant arts scene, and rich blend of Native American, Hispanic, and Anglo cultures.
- 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 Luis Triple: [La Molina, hasNeighboringDistrict, San Luis]
Generated description
San Luis is a residential and commercial district located in the eastern part of Lima, Peru.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: San Luis Target entity description: San Luis is a residential and commercial district located in the eastern part of Lima, Peru.
-
A.
Santa Fe
Santa Fe is a major modern business and financial district in western Mexico City known for its corporate offices, upscale shopping centers, and contemporary high-rise architecture.
-
B.
San Carlos
San Carlos is a city in San Mateo County, California, located on the San Francisco Peninsula between Belmont and Redwood City.
-
C.
San Carlos
San Carlos is a Nicaraguan town that serves as a key river and lake port near the southeastern end of Lake Nicaragua.
-
D.
Durango
Durango is a state in north-central Mexico known for its rugged mountainous terrain, significant mining history, and role as a setting for classic Western films.
-
E.
Santa Fe, New Mexico
Santa Fe, New Mexico is the capital city of New Mexico, renowned for its Pueblo-style architecture, vibrant arts scene, and rich blend of Native American, Hispanic, and Anglo cultures.
- 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_69a4936cb7448190914f5fe4b8d81607 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4aa9e0f0081909d2a89387d6c08e1 |
completed | March 1, 2026, 9:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a792892a588190b15b0cb95c431084 |
completed | March 4, 2026, 2:01 a.m. |
| NEDg | Description generation | batch_69a79335d99c819098c72e7a86ad1130 |
completed | March 4, 2026, 2:04 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a793c612d88190bce254142bd75f67 |
completed | March 4, 2026, 2:07 a.m. |
Created at: March 1, 2026, 7:38 p.m.