Triple

T35836453
Position Surface form Disambiguated ID Type / Status
Subject Overseas Railroad E1035952 entity
Predicate traversed P36970 FINISHED
Object Bahia Honda Bridge
Bahia Honda Bridge is a historic steel truss railroad and later highway bridge in the Florida Keys, notable for its dramatic span over the deep waters of Bahia Honda Channel.
E2164350 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: Bahia Honda Bridge | Statement: [Overseas Railroad, traversed, Bahia Honda Bridge]
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: Bahia Honda Bridge
Triple: [Overseas Railroad, traversed, Bahia Honda Bridge]
Generated description
Bahia Honda Bridge is a historic steel truss railroad and later highway bridge in the Florida Keys, notable for its dramatic span over the deep waters of Bahia Honda Channel.

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_69f76e192a94819082db360cb91e6a8d completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f7a92d4ecc81909660505985c5003a completed May 3, 2026, 7:59 p.m.
NED1 Entity disambiguation (via context triple) batch_6a38bfc2c3b481909473399d3de9e569 completed June 22, 2026, 4:53 a.m.
NEDg Description generation batch_6a38c06ea00c8190a197181f7539bb88 completed June 22, 2026, 4:56 a.m.
NED2 Entity disambiguation (via description) batch_6a38c11341d48190a70b63b26023add0 completed June 22, 2026, 4:58 a.m.
Created at: May 3, 2026, 4:06 p.m.