Triple

T25128128
Position Surface form Disambiguated ID Type / Status
Subject Traian Băsescu E629449 entity
Predicate positionHeld P8 FINISHED
Object Minister of Transport of Romania
The Minister of Transport of Romania is the government official responsible for national transport policy, infrastructure, and regulation across road, rail, air, and maritime sectors.
E174496 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: Minister of Transport of Romania | Statement: [Traian Băsescu, positionHeld, Minister of Transport of Romania]
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: Minister of Transport of Romania
Triple: [Traian Băsescu, positionHeld, Minister of Transport of Romania]
Generated description
The Minister of Transport of Romania is the government official responsible for national transport policy, infrastructure, and regulation across road, rail, air, and maritime sectors.

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_69e2ff3288048190bd82c3b7f7bd0e62 completed April 18, 2026, 3:49 a.m.
NER Named-entity recognition batch_69f465f5dac08190a76de4990c496bf6 completed May 1, 2026, 8:36 a.m.
NED1 Entity disambiguation (via context triple) batch_6a105cfa51348190bee27cbcf0f3b3bf completed May 22, 2026, 1:41 p.m.
NEDg Description generation batch_6a105e161df88190ba6a36e7581cd4ae completed May 22, 2026, 1:45 p.m.
NED2 Entity disambiguation (via description) batch_6a105fa381408190b9343fb060d29374 completed May 22, 2026, 1:52 p.m.
Created at: April 18, 2026, 6:28 a.m.