Triple

T28952865
Position Surface form Disambiguated ID Type / Status
Subject Government of the Province of Salta E731065 entity
Predicate executiveLeader P2568 FINISHED
Object Governor of Salta
The Governor of Salta is the highest-ranking political official and head of the provincial executive branch in Argentina’s Salta Province.
E1846667 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: Governor of Salta | Statement: [Government of the Province of Salta, executiveLeader, Governor of Salta]
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: Governor of Salta
Triple: [Government of the Province of Salta, executiveLeader, Governor of Salta]
Generated description
The Governor of Salta is the highest-ranking political official and head of the provincial executive branch in Argentina’s Salta Province.

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_69f043eb9bcc819091ac7b07aecb6475 completed April 28, 2026, 5:21 a.m.
NER Named-entity recognition batch_69f65bbab8648190a6c08c4eb3a0a8fa completed May 2, 2026, 8:16 p.m.
NED1 Entity disambiguation (via context triple) batch_6a251f59b500819088545dda63daf46c completed June 7, 2026, 7:35 a.m.
NEDg Description generation batch_6a2524587f4c8190866c4b0e6e8cf43a completed June 7, 2026, 7:57 a.m.
NED2 Entity disambiguation (via description) batch_6a2524b966888190a20408ad0f27f892 completed June 7, 2026, 7:58 a.m.
Created at: April 28, 2026, 8:45 a.m.