Triple

T23660350
Position Surface form Disambiguated ID Type / Status
Subject Tofo Beach E584425 entity
Predicate near P350 FINISHED
Object Tofinho
Tofinho is a small coastal village and surf spot in southern Mozambique, known for its scenic beaches, consistent waves, and laid-back atmosphere.
E1592955 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: Tofinho | Statement: [Tofo Beach, near, Tofinho]
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: Tofinho
Triple: [Tofo Beach, near, Tofinho]
Generated description
Tofinho is a small coastal village and surf spot in southern Mozambique, known for its scenic beaches, consistent waves, and laid-back atmosphere.

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_69e248ffc0888190ae23c4731eb8b7ac completed April 17, 2026, 2:51 p.m.
NER Named-entity recognition batch_69f1b35f03448190834991c2a65ef0e4 completed April 29, 2026, 7:29 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0f45b280f08190be6e5f78f1f2b1a1 completed May 21, 2026, 5:49 p.m.
NEDg Description generation batch_6a0f46d684b481908baeb3ef405e2833 completed May 21, 2026, 5:54 p.m.
NED2 Entity disambiguation (via description) batch_6a0f47c4597c81909425a8ac557a77af completed May 21, 2026, 5:58 p.m.
Created at: April 17, 2026, 6:50 p.m.