Triple

T23684488
Position Surface form Disambiguated ID Type / Status
Subject National anthem of Ecuador E585125 entity
Predicate lyricsBy P1141 FINISHED
Object Juan León Mera
Juan León Mera was a 19th-century Ecuadorian writer, politician, and intellectual best known for penning the lyrics of Ecuador’s national anthem and the novel "Cumandá."
E1606556 NE FINISHED

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: Juan León Mera | Statement: [National anthem of Ecuador, lyricsBy, Juan León Mera]
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: Juan León Mera
Triple: [National anthem of Ecuador, lyricsBy, Juan León Mera]
Generated description
Juan León Mera was a 19th-century Ecuadorian writer, politician, and intellectual best known for penning the lyrics of Ecuador’s national anthem and the novel "Cumandá."

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_69e249037ce0819088b149608e98f685 completed April 17, 2026, 2:51 p.m.
NER Named-entity recognition batch_69f1b4fb26c88190a6776e4dfd10d54c completed April 29, 2026, 7:36 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0f695bbe7881909aed23cac9f70e12 completed May 21, 2026, 8:21 p.m.
NEDg Description generation batch_6a0f6d3d0b548190aa6de291bffd32ce completed May 21, 2026, 8:38 p.m.
NED2 Entity disambiguation (via description) batch_6a0f6db3e3c081909f81db7080f51351 completed May 21, 2026, 8:40 p.m.
Created at: April 17, 2026, 6:52 p.m.