Triple

T33912897
Position Surface form Disambiguated ID Type / Status
Subject The Giant of Thunder Mountain E869364 entity
Predicate characterPortrayedBy P1507 FINISHED
Object Farley – William Sanderson
Farley, portrayed by William Sanderson, is a key character in the family adventure film "The Giant of Thunder Mountain."
E2073542 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: Farley – William Sanderson | Statement: [The Giant of Thunder Mountain, characterPortrayedBy, Farley – William Sanderson]
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: Farley – William Sanderson
Triple: [The Giant of Thunder Mountain, characterPortrayedBy, Farley – William Sanderson]
Generated description
Farley, portrayed by William Sanderson, is a key character in the family adventure film "The Giant of Thunder Mountain."

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_69f3499869bc8190b6c33a81686af226 completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f701b2987c819099855d7d71c27dec completed May 3, 2026, 8:05 a.m.
NED1 Entity disambiguation (via context triple) batch_6a36824bc1c8819090473ffdfd8ea31d completed June 20, 2026, 12:06 p.m.
NEDg Description generation batch_6a3683a2d7d881908af5589d30213ac8 completed June 20, 2026, 12:12 p.m.
NED2 Entity disambiguation (via description) batch_6a36848248c081909b5ab57a8c3accc6 completed June 20, 2026, 12:16 p.m.
Created at: May 1, 2026, 1:48 a.m.