Triple

T32049611
Position Surface form Disambiguated ID Type / Status
Subject Anapo River E818450 entity
Predicate mouthLocatedIn P417 FINISHED
Object Bay of Syracuse
The Bay of Syracuse is a coastal inlet on the eastern coast of Sicily, Italy, historically significant as the maritime setting of the ancient Greek city of Syracuse.
E1988402 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: Bay of Syracuse | Statement: [Anapo River, mouthLocatedIn, Bay of Syracuse]
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: Bay of Syracuse
Triple: [Anapo River, mouthLocatedIn, Bay of Syracuse]
Generated description
The Bay of Syracuse is a coastal inlet on the eastern coast of Sicily, Italy, historically significant as the maritime setting of the ancient Greek city of Syracuse.

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_69f348fcfb648190859f6be5e04b7cfe completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6b4c884148190be2cb7d9b354d17f completed May 3, 2026, 2:36 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2ed5014dc48190a867e1417199d589 completed June 14, 2026, 4:21 p.m.
NEDg Description generation batch_6a2ed5c14c4c8190965782d998ae7f2b completed June 14, 2026, 4:24 p.m.
NED2 Entity disambiguation (via description) batch_6a2ed747be30819082b3f0e05dc1f118 completed June 14, 2026, 4:31 p.m.
Created at: May 1, 2026, 12:20 a.m.