Triple

T27269585
Position Surface form Disambiguated ID Type / Status
Subject Luni E688008 entity
Predicate partOf P40 FINISHED
Object municipality of Luni (SP)
The municipality of Luni (SP) is a small coastal town in the province of La Spezia, Liguria, Italy, known for the nearby ancient Roman archaeological site of Luna.
E1762994 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: municipality of Luni (SP) | Statement: [Luni, partOf, municipality of Luni (SP)]
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: municipality of Luni (SP)
Triple: [Luni, partOf, municipality of Luni (SP)]
Generated description
The municipality of Luni (SP) is a small coastal town in the province of La Spezia, Liguria, Italy, known for the nearby ancient Roman archaeological site of Luna.

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_69ef3557abc481908bf3c146f0f3356a completed April 27, 2026, 10:07 a.m.
NER Named-entity recognition batch_69f6272167c481909ca7783afdf7e14e completed May 2, 2026, 4:32 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12628b6a148190879f74e1ac22ffc8 completed May 24, 2026, 2:29 a.m.
NEDg Description generation batch_6a1266920d008190b029acd1c8efc214 completed May 24, 2026, 2:46 a.m.
NED2 Entity disambiguation (via description) batch_6a1266f0b7448190a158f776016efacd completed May 24, 2026, 2:48 a.m.
Created at: April 27, 2026, 10:58 a.m.