Triple

T24387706
Position Surface form Disambiguated ID Type / Status
Subject Tomebamba River E614792 entity
Predicate hasBridge P386 FINISHED
Object Puente de Todos Santos
Puente de Todos Santos is a historic bridge in Cuenca, Ecuador, spanning the Tomebamba River and connecting the city’s colonial center with the riverbank area.
E1636847 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: Puente de Todos Santos | Statement: [Tomebamba River, hasBridge, Puente de Todos Santos]
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: Puente de Todos Santos
Triple: [Tomebamba River, hasBridge, Puente de Todos Santos]
Generated description
Puente de Todos Santos is a historic bridge in Cuenca, Ecuador, spanning the Tomebamba River and connecting the city’s colonial center with the riverbank area.

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_69e2d7e362e481909e32fe4ef8269d4f completed April 18, 2026, 1:01 a.m.
NER Named-entity recognition batch_69f29455e7fc8190841f909b970f6bd3 completed April 29, 2026, 11:29 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0fee63763481908914c29f168cff11 completed May 22, 2026, 5:49 a.m.
NEDg Description generation batch_6a0fef3ca1e4819093c95f497eb37e82 completed May 22, 2026, 5:53 a.m.
NED2 Entity disambiguation (via description) batch_6a0feff2170481909764b1d8ab9f0afc completed May 22, 2026, 5:56 a.m.
Created at: April 18, 2026, 2:03 a.m.