Triple

T26785857
Position Surface form Disambiguated ID Type / Status
Subject Isabella Garcia-Shapiro E670375 entity
Predicate friend P8712 FINISHED
Object Ginger Hirano
Ginger Hirano is a shy, intelligent girl from the animated series "Phineas and Ferb," known for her crush on Baljeet and her close friendships within the neighborhood kids' group.
E1919828 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: Ginger Hirano | Statement: [Isabella Garcia-Shapiro, friend, Ginger Hirano]
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: Ginger Hirano
Triple: [Isabella Garcia-Shapiro, friend, Ginger Hirano]
Generated description
Ginger Hirano is a shy, intelligent girl from the animated series "Phineas and Ferb," known for her crush on Baljeet and her close friendships within the neighborhood kids' group.

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_69eeb31d45f8819089f52ebdbc556218 completed April 27, 2026, 12:51 a.m.
NER Named-entity recognition batch_69f6197fccd0819097d2a402003b05ab completed May 2, 2026, 3:34 p.m.
NED1 Entity disambiguation (via context triple) batch_6a27be472cb08190a04fd8cf631a03a9 completed June 9, 2026, 7:18 a.m.
NEDg Description generation batch_6a27c1e7e08881909adc8884524ff1f2 completed June 9, 2026, 7:34 a.m.
NED2 Entity disambiguation (via description) batch_6a27c56068d88190ac70d4300b5a1cad completed June 9, 2026, 7:48 a.m.
Created at: April 27, 2026, 4:13 a.m.