Triple

T24556010
Position Surface form Disambiguated ID Type / Status
Subject Alan Harper E607517 entity
Predicate hasRomanticRelationshipWith P9994 FINISHED
Object Lyndsey McElroy
Lyndsey McElroy is a recurring character on the sitcom "Two and a Half Men," known as one of Alan Harper's primary love interests and a single mother with a complicated on-and-off relationship with him.
E1706317 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: Lyndsey McElroy | Statement: [Alan Harper, hasRomanticRelationshipWith, Lyndsey McElroy]
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: Lyndsey McElroy
Triple: [Alan Harper, hasRomanticRelationshipWith, Lyndsey McElroy]
Generated description
Lyndsey McElroy is a recurring character on the sitcom "Two and a Half Men," known as one of Alan Harper's primary love interests and a single mother with a complicated on-and-off relationship with him.

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_69e2c4cae1b88190825e88d5ce8aa61e completed April 17, 2026, 11:39 p.m.
NER Named-entity recognition batch_69f2a8f1fb9c819086b5bd0b03a853e6 completed April 30, 2026, 12:57 a.m.
NED1 Entity disambiguation (via context triple) batch_6a111ad9cbe08190925ec0b46db7ff45 completed May 23, 2026, 3:11 a.m.
NEDg Description generation batch_6a111ba170c881908916feb646df7338 completed May 23, 2026, 3:14 a.m.
NED2 Entity disambiguation (via description) batch_6a111c1129588190918ec8f98cad6fd4 completed May 23, 2026, 3:16 a.m.
Created at: April 18, 2026, 2:27 a.m.