Triple

T15329381
Position Surface form Disambiguated ID Type / Status
Subject San Luis Province E366492 entity
Predicate capital P234 FINISHED
Object San Luis (city)
San Luis is a mid-sized Argentine city in the Cuyo region, known for its colonial architecture, surrounding sierras, and role as an administrative and commercial hub.
 E366492 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 (city) | Statement: [San Luis Province, capital, San Luis (city)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: San Luis (city)
Context triple: [San Luis Province, capital, San Luis (city)]
  • A. San Luis
    San Luis is a barangay (village-level administrative division) within the municipality of Capul in the Philippines.
  • B. San Luis
    San Luis is a town and municipality located in the Comayagua Department of central Honduras.
  • C. San Luis
    San Luis is a municipality and town in western Cuba known for its agricultural activities within Pinar del Río Province.
  • D. San Luis
    San Luis is a province in central Argentina known for its mountainous landscapes, arid climate, and role in the country’s early independence era.
  • E. San Luis
    San Luis is a town on the southeastern coast of Menorca in Spain’s Balearic Islands, known for its whitewashed architecture and nearby beaches.
  • 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 (city)
Triple: [San Luis Province, capital, San Luis (city)]
Generated description
San Luis is a mid-sized Argentine city in the Cuyo region, known for its colonial architecture, surrounding sierras, and role as an administrative and commercial hub.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: San Luis (city)
Target entity description: San Luis is a mid-sized Argentine city in the Cuyo region, known for its colonial architecture, surrounding sierras, and role as an administrative and commercial hub.
  • A. San Luis
    San Luis is a barangay (village-level administrative division) within the municipality of Capul in the Philippines.
  • B. San Luis
    San Luis is a town and municipality located in the Comayagua Department of central Honduras.
  • C. San Luis
    San Luis is a municipality and town in western Cuba known for its agricultural activities within Pinar del Río Province.
  • D. San Luis chosen
    San Luis is a province in central Argentina known for its mountainous landscapes, arid climate, and role in the country’s early independence era.
  • E. San Luis
    San Luis is a town on the southeastern coast of Menorca in Spain’s Balearic Islands, known for its whitewashed architecture and nearby beaches.
  • F. None of above.

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_69d85a121520819093dcce999fdefe1a completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e03e0161ac8190aa1d52c063c02ad0 completed April 16, 2026, 1:40 a.m.
NED1 Entity disambiguation (via context triple) batch_69fef8b1b2d08190a158bf65535ad750 completed May 9, 2026, 9:04 a.m.
NEDg Description generation batch_69fefb10ba78819094948f5401702e79 completed May 9, 2026, 9:14 a.m.
NED2 Entity disambiguation (via description) batch_69fefbad7de08190aa2479ec0243e3a6 completed May 9, 2026, 9:17 a.m.
Created at: April 10, 2026, 3:16 a.m.