Triple

T23813408
Position Surface form Disambiguated ID Type / Status
Subject Battleship Parkway E589022 entity
Predicate alsoKnownAs P39 FINISHED
Object Mobile Bay Causeway
Mobile Bay Causeway is a low, multi-lane highway crossing the northern part of Mobile Bay in Alabama, carrying U.S. Route 90 and U.S. Route 98 between Mobile and the eastern shore.
E1605664 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: Mobile Bay Causeway | Statement: [Battleship Parkway, alsoKnownAs, Mobile Bay Causeway]
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: Mobile Bay Causeway
Triple: [Battleship Parkway, alsoKnownAs, Mobile Bay Causeway]
Generated description
Mobile Bay Causeway is a low, multi-lane highway crossing the northern part of Mobile Bay in Alabama, carrying U.S. Route 90 and U.S. Route 98 between Mobile and the eastern shore.

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_69e25d18619081909c7fb89d8926f14a completed April 17, 2026, 4:17 p.m.
NER Named-entity recognition batch_69f1c7a911f481909c8a98a5aec72b4b completed April 29, 2026, 8:56 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0f6982e8f081909441a66447410bcd completed May 21, 2026, 8:22 p.m.
NEDg Description generation batch_6a0f6d3ea7a0819098e47bce047df2c7 completed May 21, 2026, 8:38 p.m.
NED2 Entity disambiguation (via description) batch_6a0f6e661d04819090ed01c4813ea238 completed May 21, 2026, 8:43 p.m.
Created at: April 17, 2026, 7:57 p.m.