Triple

T28314652
Position Surface form Disambiguated ID Type / Status
Subject Meis E714099 entity
Predicate hasPort P35 FINISHED
Object Kastellorizo port
Kastellorizo port is the small harbor serving the Greek island of Kastellorizo (Meis), known for its picturesque waterfront, colorful houses, and role as the island’s main gateway for boats and ferries.
E1829277 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: Kastellorizo port | Statement: [Meis, hasPort, Kastellorizo port]
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: Kastellorizo port
Triple: [Meis, hasPort, Kastellorizo port]
Generated description
Kastellorizo port is the small harbor serving the Greek island of Kastellorizo (Meis), known for its picturesque waterfront, colorful houses, and role as the island’s main gateway for boats and ferries.

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_69efb5256afc8190b9322d25c3ae6320 completed April 27, 2026, 7:12 p.m.
NER Named-entity recognition batch_69f644e49c448190a394f783d9fc3129 completed May 2, 2026, 6:39 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1cc35c5c74819090fa8d0ba176cf87 completed May 31, 2026, 11:25 p.m.
NEDg Description generation batch_6a1cc4a74dec8190ab3ce653f778ec13 completed May 31, 2026, 11:30 p.m.
NED2 Entity disambiguation (via description) batch_6a1cc544e60081908682c3750e6ac83d completed May 31, 2026, 11:33 p.m.
Created at: April 27, 2026, 11:42 p.m.