Triple

T30381401
Position Surface form Disambiguated ID Type / Status
Subject Alec R. Costandinos E772840 entity
Predicate associatedAct P37 FINISHED
Object Sphinx
Sphinx is a disco music project best known for its work with French producer and composer Alec R. Costandinos during the 1970s.
E1912641 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: Sphinx | Statement: [Alec R. Costandinos, associatedAct, Sphinx]
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: Sphinx
Triple: [Alec R. Costandinos, associatedAct, Sphinx]
Generated description
Sphinx is a disco music project best known for its work with French producer and composer Alec R. Costandinos during the 1970s.

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_69f2248e3444819081b05712dc6873de completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f685198e5c8190b0b93408ec7cab1b completed May 2, 2026, 11:13 p.m.
NED1 Entity disambiguation (via context triple) batch_6a27894a754c8190933f19e97580c90c completed June 9, 2026, 3:32 a.m.
NEDg Description generation batch_6a278aa2bd7c8190bc7dca88c989e806 completed June 9, 2026, 3:38 a.m.
NED2 Entity disambiguation (via description) batch_6a278b9c83b48190bbb2c6d6fe36ff82 completed June 9, 2026, 3:42 a.m.
Created at: April 29, 2026, 8 p.m.