Triple

T36922908
Position Surface form Disambiguated ID Type / Status
Subject Abigail Spencer E913253 entity
Predicate parent P120 FINISHED
Object Yancy Spencer III
Yancy Spencer III was a pioneering American surfer often credited with helping popularize the sport along the Gulf Coast and is also known as the father of actress Abigail Spencer.
E2204624 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: Yancy Spencer III | Statement: [Abigail Spencer, parent, Yancy Spencer III]
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: Yancy Spencer III
Triple: [Abigail Spencer, parent, Yancy Spencer III]
Generated description
Yancy Spencer III was a pioneering American surfer often credited with helping popularize the sport along the Gulf Coast and is also known as the father of actress Abigail Spencer.

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_69f76e885b848190bad82c87e9525486 completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69f9fdcde388819099c0d417f07b5a60 completed May 5, 2026, 2:25 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3e1631b830819081a748114919ef33 completed June 26, 2026, 6:03 a.m.
NEDg Description generation batch_6a3e16c86a84819085a695e70971c83b completed June 26, 2026, 6:06 a.m.
NED2 Entity disambiguation (via description) batch_6a3e1de0bf6c819085b7d2ac2759776c completed June 26, 2026, 6:36 a.m.
Created at: May 3, 2026, 4:13 p.m.