Triple

T34499822
Position Surface form Disambiguated ID Type / Status
Subject Voluntari E885715 entity
Predicate hasRival P1375 FINISHED
Object FC Academica Clinceni
FC Academica Clinceni is a Romanian professional football club based in Clinceni, known for competing in the country’s top leagues and for its local rivalry with FC Voluntari.
E2103222 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: FC Academica Clinceni | Statement: [Voluntari, hasRival, FC Academica Clinceni]
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: FC Academica Clinceni
Triple: [Voluntari, hasRival, FC Academica Clinceni]
Generated description
FC Academica Clinceni is a Romanian professional football club based in Clinceni, known for competing in the country’s top leagues and for its local rivalry with FC Voluntari.

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_69f349cc0220819081f154c6964f4dc2 completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69f71f50f7dc8190bccff0a2fe80da6e completed May 3, 2026, 10:11 a.m.
NED1 Entity disambiguation (via context triple) batch_6a3740f957ec81909a1226768a228907 completed June 21, 2026, 1:40 a.m.
NEDg Description generation batch_6a374189e1b881908f19247a3a1104d2 completed June 21, 2026, 1:42 a.m.
NED2 Entity disambiguation (via description) batch_6a3741f66d88819081e0566ae6ded487 completed June 21, 2026, 1:44 a.m.
Created at: May 1, 2026, 2:01 a.m.