Triple

T28057645
Position Surface form Disambiguated ID Type / Status
Subject Eisenhower Science and Technology Leadership Academy E709008 entity
Predicate county P75 FINISHED
Object Montgomery County
Montgomery County is a populous suburban county in southeastern Pennsylvania, known for its mix of residential communities, commercial centers, and strong public school systems just northwest of Philadelphia.
E226281 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: Montgomery County | Statement: [Eisenhower Science and Technology Leadership Academy, county, Montgomery County]
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: Montgomery County
Triple: [Eisenhower Science and Technology Leadership Academy, county, Montgomery County]
Generated description
Montgomery County is a populous suburban county in southeastern Pennsylvania, known for its mix of residential communities, commercial centers, and strong public school systems just northwest of Philadelphia.

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_69ef9b6df9f48190bbb971d02cbe1b65 completed April 27, 2026, 5:22 p.m.
NER Named-entity recognition batch_69f63fdd77f48190ad4f34abf27206b7 completed May 2, 2026, 6:18 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1606f8b2ec81908756ba64251660bc completed May 26, 2026, 8:47 p.m.
NEDg Description generation batch_6a160bbebed08190a74629bda23c2eaa completed May 26, 2026, 9:08 p.m.
NED2 Entity disambiguation (via description) batch_6a160e178f8881908d7d4b85b2e8a2c1 completed May 26, 2026, 9:18 p.m.
Created at: April 27, 2026, 8:37 p.m.