Triple

T23893082
Position Surface form Disambiguated ID Type / Status
Subject Festival Ludique International de Parthenay E600828 entity
Predicate alsoKnownAs P39 FINISHED
Object FLIP de Parthenay
FLIP de Parthenay is a major annual international games festival held in Parthenay, France, featuring a wide range of board, role-playing, and outdoor games throughout the town.
E1607503 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: FLIP de Parthenay | Statement: [Festival Ludique International de Parthenay, alsoKnownAs, FLIP de Parthenay]
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: FLIP de Parthenay
Triple: [Festival Ludique International de Parthenay, alsoKnownAs, FLIP de Parthenay]
Generated description
FLIP de Parthenay is a major annual international games festival held in Parthenay, France, featuring a wide range of board, role-playing, and outdoor games throughout the town.

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_69e295341ac0819080647f2908af793c completed April 17, 2026, 8:16 p.m.
NER Named-entity recognition batch_69f1cd050db8819090aa268ba7e5eeed completed April 29, 2026, 9:19 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0f7626c0008190915e8c9b6f80f8bf completed May 21, 2026, 9:16 p.m.
NEDg Description generation batch_6a0f76cc78748190b0f22716094bba19 completed May 21, 2026, 9:19 p.m.
NED2 Entity disambiguation (via description) batch_6a0f77541b948190bb866a8c7c6f5ca9 completed May 21, 2026, 9:21 p.m.
Created at: April 17, 2026, 8:25 p.m.