Triple

T24877530
Position Surface form Disambiguated ID Type / Status
Subject Pantai Akkarena E622613 entity
Predicate locatedIn P40 FINISHED
Object Makassar Strait coast
The Makassar Strait coast is a coastal region along the narrow sea channel separating the islands of Borneo and Sulawesi in Indonesia, known for its beaches, ports, and maritime trade routes.
E1649176 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: Makassar Strait coast | Statement: [Pantai Akkarena, locatedIn, Makassar Strait coast]
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: Makassar Strait coast
Triple: [Pantai Akkarena, locatedIn, Makassar Strait coast]
Generated description
The Makassar Strait coast is a coastal region along the narrow sea channel separating the islands of Borneo and Sulawesi in Indonesia, known for its beaches, ports, and maritime trade routes.

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_69e2fac3fdbc81909c2ec49be5743cd9 completed April 18, 2026, 3:30 a.m.
NER Named-entity recognition batch_69f42320ff348190ae6f58953a2c7a3c completed May 1, 2026, 3:50 a.m.
NED1 Entity disambiguation (via context triple) batch_6a101c63f23081908c25303c4ac86063 completed May 22, 2026, 9:05 a.m.
NEDg Description generation batch_6a1022daf24481908f3a86a212a1b9bf completed May 22, 2026, 9:33 a.m.
NED2 Entity disambiguation (via description) batch_6a10234dcc988190a2dfed33d61cba58 completed May 22, 2026, 9:35 a.m.
Created at: April 18, 2026, 5:24 a.m.