Triple

T30799203
Position Surface form Disambiguated ID Type / Status
Subject Lidra Caddesi E784318 entity
Predicate hasNameInGreek P3659 FINISHED
Object Lidras Street
Lidras Street is a historic and bustling pedestrian shopping street in central Nicosia, Cyprus, known for crossing the Green Line between the island’s Greek Cypriot and Turkish Cypriot sectors.
 E1957702 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: Lidras Street | Statement: [Lidra Caddesi, hasNameInGreek, Lidras Street]
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: Lidras Street
Triple: [Lidra Caddesi, hasNameInGreek, Lidras Street]
Generated description
Lidras Street is a historic and bustling pedestrian shopping street in central Nicosia, Cyprus, known for crossing the Green Line between the island’s Greek Cypriot and Turkish Cypriot sectors.

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_69f224b3a7ec819096939414d103e31e completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f6903998008190a77f8503d88c50d8 completed May 3, 2026, midnight
NED1 Entity disambiguation (via context triple) batch_6a2a71ea008c8190ba8c2d2fbd3cfe1c completed June 11, 2026, 8:29 a.m.
NEDg Description generation batch_6a2a75e9f758819088481639f461a9f6 completed June 11, 2026, 8:46 a.m.
NED2 Entity disambiguation (via description) batch_6a2a8d02ade88190b2d3d2212e4fea16 completed June 11, 2026, 10:25 a.m.
Created at: April 29, 2026, 8:42 p.m.