Triple

T31198421
Position Surface form Disambiguated ID Type / Status
Subject Palmer Cortlandt E795395 entity
Predicate businessInterest P3849 FINISHED
Object Cortlandt Electronics
Cortlandt Electronics is a fictional electronics company owned by wealthy businessman Palmer Cortlandt in the soap opera "All My Children."
E1951490 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: Cortlandt Electronics | Statement: [Palmer Cortlandt, businessInterest, Cortlandt Electronics]
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: Cortlandt Electronics
Triple: [Palmer Cortlandt, businessInterest, Cortlandt Electronics]
Generated description
Cortlandt Electronics is a fictional electronics company owned by wealthy businessman Palmer Cortlandt in the soap opera "All My Children."

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_69f224d7a6a481908187c4362a8a525f completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f69bc10244819091bf44141c50a566 completed May 3, 2026, 12:50 a.m.
NED1 Entity disambiguation (via context triple) batch_6a29591c91e4819087aa0ff63400e937 completed June 10, 2026, 12:31 p.m.
NEDg Description generation batch_6a295d2ada288190aaf4ba844b770666 completed June 10, 2026, 12:48 p.m.
NED2 Entity disambiguation (via description) batch_6a295e13ebbc8190bba5d5efe052b6ea completed June 10, 2026, 12:52 p.m.
Created at: April 29, 2026, 9:09 p.m.