Triple

T24177272
Position Surface form Disambiguated ID Type / Status
Subject Top of the World Observation Level E599315 entity
Predicate hasAlternateName P39 FINISHED
Object Top of the World Observation Deck
Top of the World Observation Deck is a public viewing platform in Baltimore’s World Trade Center offering panoramic views of the city and its harbor.
E1620000 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: Top of the World Observation Deck | Statement: [Top of the World Observation Level, hasAlternateName, Top of the World Observation Deck]
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: Top of the World Observation Deck
Triple: [Top of the World Observation Level, hasAlternateName, Top of the World Observation Deck]
Generated description
Top of the World Observation Deck is a public viewing platform in Baltimore’s World Trade Center offering panoramic views of the city and its harbor.

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_69e288cca05481908faeb1563711114a completed April 17, 2026, 7:23 p.m.
NER Named-entity recognition batch_69f1e1d24bec8190aab8d513c10e8210 completed April 29, 2026, 10:47 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0fad4119c4819084b2e7c1c7120f96 completed May 22, 2026, 1:11 a.m.
NEDg Description generation batch_6a0fae2e5188819084da9d0a77697c72 completed May 22, 2026, 1:15 a.m.
NED2 Entity disambiguation (via description) batch_6a0faecda22881909d9617138ceca0d9 completed May 22, 2026, 1:18 a.m.
Created at: April 17, 2026, 11:34 p.m.