Triple

T28376949
Position Surface form Disambiguated ID Type / Status
Subject Grizzly Peak Airfield E718778 entity
Predicate formerlyKnownAs P65 FINISHED
Object Condor Flats
Condor Flats was an aviation-themed land at Disney California Adventure Park, centered around a desert airfield motif and attractions like the original Soarin’ Over California.
E1814492 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: Condor Flats | Statement: [Grizzly Peak Airfield, formerlyKnownAs, Condor Flats]
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: Condor Flats
Triple: [Grizzly Peak Airfield, formerlyKnownAs, Condor Flats]
Generated description
Condor Flats was an aviation-themed land at Disney California Adventure Park, centered around a desert airfield motif and attractions like the original Soarin’ Over 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_69eff6ee5afc8190bd7375a29f0cc6c6 completed April 27, 2026, 11:53 p.m.
NER Named-entity recognition batch_69f64c5eee988190aa18cd909ea3e855 completed May 2, 2026, 7:11 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1627db13888190bb639b568ea7b572 completed May 26, 2026, 11:08 p.m.
NEDg Description generation batch_6a1628bdc5ac81909d5f7dbdfad7934c completed May 26, 2026, 11:11 p.m.
NED2 Entity disambiguation (via description) batch_6a16294f42508190aac4e3617131dafe completed May 26, 2026, 11:14 p.m.
Created at: April 28, 2026, 1:03 a.m.