Triple

T37892565
Position Surface form Disambiguated ID Type / Status
Subject Christina Haack E945187 entity
Predicate alsoKnownAs P39 FINISHED
Object Christina Anstead
Christina Anstead is an American real estate investor and television personality best known as the co-host of the HGTV series "Flip or Flop" and star of "Christina on the Coast."
E2275830 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: Christina Anstead | Statement: [Christina Haack, alsoKnownAs, Christina Anstead]
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: Christina Anstead
Triple: [Christina Haack, alsoKnownAs, Christina Anstead]
Generated description
Christina Anstead is an American real estate investor and television personality best known as the co-host of the HGTV series "Flip or Flop" and star of "Christina on the Coast."

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_69f76ef0e8708190987c7254ed8c7abe completed May 3, 2026, 3:51 p.m.
NER Named-entity recognition batch_69fbbd361fe08190afc3ef4e720304be completed May 6, 2026, 10:14 p.m.
NED1 Entity disambiguation (via context triple) batch_6a41ea7347308190bf4a1ef3c836bdda completed June 29, 2026, 3:45 a.m.
NEDg Description generation batch_6a41eb116f288190bb2cc9876dea0577 completed June 29, 2026, 3:48 a.m.
NED2 Entity disambiguation (via description) batch_6a41eb7dc3cc8190955444ba736583de completed June 29, 2026, 3:50 a.m.
Created at: May 3, 2026, 4:19 p.m.