Triple

T16935886

Position	Surface form	Disambiguated ID	Type / Status
Subject	Kuşadası	`E410825`	entity
Predicate	hasNearby	`P350`	FINISHED
Object	Güvercinada Island Güvercinada Island is a small historic islet off the coast of Kuşadası in western Turkey, known for its Ottoman-era fortress and scenic views of the Aegean Sea.	`E1975115`	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: Güvercinada Island | Statement: [Kuşadası, hasNearby, Güvercinada Island]

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: Güvercinada Island
Triple: [Kuşadası, hasNearby, Güvercinada Island]

Generated description

Güvercinada Island is a small historic islet off the coast of Kuşadası in western Turkey, known for its Ottoman-era fortress and scenic views of the Aegean Sea.

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_69d886c886688190967be07322597ac9`	completed	April 10, 2026, 5:12 a.m.
NER	Named-entity recognition	`batch_69e3cf2a05f48190a0a8ac86985f4000`	completed	April 18, 2026, 6:36 p.m.
NED1	Entity disambiguation (via context triple)	`batch_6a2b9448def48190b948c9f4dd6a0fa5`	completed	June 12, 2026, 5:08 a.m.
NEDg	Description generation	`batch_6a2b950959f48190ad19907e9c9a64c6`	completed	June 12, 2026, 5:11 a.m.
NED2	Entity disambiguation (via description)	`batch_6a2b957d073081909a1657bd313ad8cd`	completed	June 12, 2026, 5:13 a.m.

Created at: April 10, 2026, 5:30 a.m.