Triple

T34664615
Position Surface form Disambiguated ID Type / Status
Subject Sam Cane E890217 entity
Predicate fullName P16 FINISHED
Object Samuel Jordan Cane
Samuel Jordan Cane is a New Zealand rugby union player best known for captaining the All Blacks as a hard-tackling openside flanker.
E2106686 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: Samuel Jordan Cane | Statement: [Sam Cane, fullName, Samuel Jordan Cane]
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: Samuel Jordan Cane
Triple: [Sam Cane, fullName, Samuel Jordan Cane]
Generated description
Samuel Jordan Cane is a New Zealand rugby union player best known for captaining the All Blacks as a hard-tackling openside flanker.

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_69f349d9c59481908b36baa0be093aea completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69f722f574388190b75d8c00917bb6f5 completed May 3, 2026, 10:27 a.m.
NED1 Entity disambiguation (via context triple) batch_6a374903aa648190b9beaf59b4562d53 completed June 21, 2026, 2:14 a.m.
NEDg Description generation batch_6a374a91d4f08190bc2df424a4136b3d completed June 21, 2026, 2:21 a.m.
NED2 Entity disambiguation (via description) batch_6a374b44cba88190999dede2bc2a408e completed June 21, 2026, 2:24 a.m.
Created at: May 1, 2026, 2:04 a.m.