Triple

T23824258
Position Surface form Disambiguated ID Type / Status
Subject Giovanni Sforza E589322 entity
Predicate positionHeld P8 FINISHED
Object Lord of Gradara
Lord of Gradara was an Italian noble title associated with the Sforza family’s rule over the fortified town of Gradara in the Marche region during the Renaissance.
E1602985 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: Lord of Gradara | Statement: [Giovanni Sforza, positionHeld, Lord of Gradara]
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: Lord of Gradara
Triple: [Giovanni Sforza, positionHeld, Lord of Gradara]
Generated description
Lord of Gradara was an Italian noble title associated with the Sforza family’s rule over the fortified town of Gradara in the Marche region during the Renaissance.

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_69e25d1922d481909cab567c06a802ab completed April 17, 2026, 4:17 p.m.
NER Named-entity recognition batch_69f1c7f04bdc8190842a287a86b60d3a completed April 29, 2026, 8:57 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0f699ab3548190ab4928e97fabe104 completed May 21, 2026, 8:22 p.m.
NEDg Description generation batch_6a0f6a2b96048190b3f1e6465232f4ba completed May 21, 2026, 8:25 p.m.
NED2 Entity disambiguation (via description) batch_6a0f6d4eddf0819081caec7518121664 completed May 21, 2026, 8:38 p.m.
Created at: April 17, 2026, 7:59 p.m.