Triple

T29413126
Position Surface form Disambiguated ID Type / Status
Subject Philippe, Duke of Anjou (1730–1733) E745949 entity
Predicate birthName P65 FINISHED
Object Philippe de France
Philippe de France was a short-lived French prince of the Bourbon dynasty, born as the second son of King Louis XV and Queen Marie Leszczyńska.
E1883259 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: Philippe de France | Statement: [Philippe, Duke of Anjou (1730–1733), birthName, Philippe de France]
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: Philippe de France
Triple: [Philippe, Duke of Anjou (1730–1733), birthName, Philippe de France]
Generated description
Philippe de France was a short-lived French prince of the Bourbon dynasty, born as the second son of King Louis XV and Queen Marie Leszczyńska.

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_69f0a79f6d5c8190a350baed0157e06f completed April 28, 2026, 12:27 p.m.
NER Named-entity recognition batch_69f66a3a4bcc8190b0a58320a08d1b13 completed May 2, 2026, 9:18 p.m.
NED1 Entity disambiguation (via context triple) batch_6a26c8cea0608190bff36e52c0810fb2 completed June 8, 2026, 1:51 p.m.
NEDg Description generation batch_6a26cde8bf4881908eddc5d71aa18574 completed June 8, 2026, 2:12 p.m.
NED2 Entity disambiguation (via description) batch_6a26d4fdf4748190a55abffb49353103 completed June 8, 2026, 2:43 p.m.
Created at: April 28, 2026, 2:58 p.m.