Triple

T26278151
Position Surface form Disambiguated ID Type / Status
Subject Lake Maracaibo Bridge E660630 entity
Predicate crosses P416 FINISHED
Object Tablazo Strait
Tablazo Strait is a narrow body of water in northwestern Venezuela that connects Lake Maracaibo to the Gulf of Venezuela and the Caribbean Sea.
E1747596 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: Tablazo Strait | Statement: [Lake Maracaibo Bridge, crosses, Tablazo Strait]
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: Tablazo Strait
Triple: [Lake Maracaibo Bridge, crosses, Tablazo Strait]
Generated description
Tablazo Strait is a narrow body of water in northwestern Venezuela that connects Lake Maracaibo to the Gulf of Venezuela and the Caribbean Sea.

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_69ee812960d081909cff6085cc9fa3a6 completed April 26, 2026, 9:18 p.m.
NER Named-entity recognition batch_69f60e36ff9c8190843bdf03b6de6b07 completed May 2, 2026, 2:46 p.m.
NED1 Entity disambiguation (via context triple) batch_6a121e73078c819090458adc6bcc7c55 completed May 23, 2026, 9:38 p.m.
NEDg Description generation batch_6a121f7b308c8190a2667f99b45cf2ab completed May 23, 2026, 9:43 p.m.
NED2 Entity disambiguation (via description) batch_6a12203ee42c8190be6d4c4d9f0ec859 completed May 23, 2026, 9:46 p.m.
Created at: April 26, 2026, 9:57 p.m.