Triple

T37094591
Position Surface form Disambiguated ID Type / Status
Subject Lentini E918524 entity
Predicate locatedNear P294 FINISHED
Object Gulf of Catania
The Gulf of Catania is a large bay on the eastern coast of Sicily, Italy, opening into the Ionian Sea near the city of Catania.
E2217382 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: Gulf of Catania | Statement: [Lentini, locatedNear, Gulf of Catania]
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: Gulf of Catania
Triple: [Lentini, locatedNear, Gulf of Catania]
Generated description
The Gulf of Catania is a large bay on the eastern coast of Sicily, Italy, opening into the Ionian Sea near the city of Catania.

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_69f76e9a48bc8190a3947508d8bca408 completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69fb2fd2f704819087cfb7d59c3d7a56 completed May 6, 2026, 12:10 p.m.
NED1 Entity disambiguation (via context triple) batch_6a403601f0c48190b815f9a7d01fdc0f completed June 27, 2026, 8:43 p.m.
NEDg Description generation batch_6a40370e29b88190896e161008cb4262 completed June 27, 2026, 8:48 p.m.
NED2 Entity disambiguation (via description) batch_6a4038978d88819094f50792d0db95ee completed June 27, 2026, 8:54 p.m.
Created at: May 3, 2026, 4:14 p.m.