Triple

T32191538
Position Surface form Disambiguated ID Type / Status
Subject Universal Studios backlot E822266 entity
Predicate hasStreetSet P72421 FINISHED
Object Western Street
Western Street is a classic Old West-style outdoor film set located on the Universal Studios backlot, frequently used as a backdrop for Western movies and television shows.
 E1997212 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: Western Street | Statement: [Universal Studios backlot, hasStreetSet, Western Street]
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: Western Street
Triple: [Universal Studios backlot, hasStreetSet, Western Street]
Generated description
Western Street is a classic Old West-style outdoor film set located on the Universal Studios backlot, frequently used as a backdrop for Western movies and television shows.

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_69f3490819cc81909bae1f8ce99423c5 completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69fef21e176c8190b307346794922551 completed May 9, 2026, 8:36 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2f3b8baaa88190ab6b21cdccb9103d completed June 14, 2026, 11:38 p.m.
NEDg Description generation batch_6a2f3cb660408190be91963d2c197ae5 completed June 14, 2026, 11:43 p.m.
NED2 Entity disambiguation (via description) batch_6a2f3f0709708190bafa7dc0708d64b4 completed June 14, 2026, 11:53 p.m.
Created at: May 1, 2026, 12:35 a.m.