Triple

T24146803
Position Surface form Disambiguated ID Type / Status
Subject Luxembourg Stock Exchange E598408 entity
Predicate operates P24 FINISHED
Object Luxembourg Green Exchange
Luxembourg Green Exchange is a pioneering platform dedicated to listing and trading green, social, and sustainable financial instruments, recognized as one of the first and leading hubs for sustainable finance globally.
E1620912 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: Luxembourg Green Exchange | Statement: [Luxembourg Stock Exchange, operates, Luxembourg Green Exchange]
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: Luxembourg Green Exchange
Triple: [Luxembourg Stock Exchange, operates, Luxembourg Green Exchange]
Generated description
Luxembourg Green Exchange is a pioneering platform dedicated to listing and trading green, social, and sustainable financial instruments, recognized as one of the first and leading hubs for sustainable finance globally.

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_69e288c9e488819093dd1acd91b08b8a completed April 17, 2026, 7:23 p.m.
NER Named-entity recognition batch_69f1e00b00708190bcd1d0b855230378 completed April 29, 2026, 10:40 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0fad2c4ec88190aa5f21a659f60af4 completed May 22, 2026, 1:11 a.m.
NEDg Description generation batch_6a0fae10893c819092a3ecd95b6b9198 completed May 22, 2026, 1:14 a.m.
NED2 Entity disambiguation (via description) batch_6a0faf345eac8190b8a648c3add470bd completed May 22, 2026, 1:19 a.m.
Created at: April 17, 2026, 11:29 p.m.