Triple

T32818463
Position Surface form Disambiguated ID Type / Status
Subject Los Alamitos Unified School District E839366 entity
Predicate hasSchool P113 FINISHED
Object Los Alamitos Elementary School
Los Alamitos Elementary School is a public elementary school serving early-grade students in the Los Alamitos area of Southern California.
E2025006 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: Los Alamitos Elementary School | Statement: [Los Alamitos Unified School District, hasSchool, Los Alamitos Elementary School]
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: Los Alamitos Elementary School
Triple: [Los Alamitos Unified School District, hasSchool, Los Alamitos Elementary School]
Generated description
Los Alamitos Elementary School is a public elementary school serving early-grade students in the Los Alamitos area of Southern California.

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_69f3493df9008190a8f5d843dcd77704 completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69f6cdd27c44819091d45e31f4b67e64 completed May 3, 2026, 4:23 a.m.
NED1 Entity disambiguation (via context triple) batch_6a34bcf232f481909e3c232db55a7978 completed June 19, 2026, 3:52 a.m.
NEDg Description generation batch_6a34bda4d1308190932b182fc3daee1f completed June 19, 2026, 3:55 a.m.
NED2 Entity disambiguation (via description) batch_6a34be47ee3c81909adac4069e76e8c4 completed June 19, 2026, 3:58 a.m.
Created at: May 1, 2026, 1:15 a.m.