Triple

T37087642
Position Surface form Disambiguated ID Type / Status
Subject Opposition (India) E918332 entity
Predicate relatedConcept P37 FINISHED
Object ruling party (India)
The ruling party in India is the political party or coalition that holds a majority in the Lok Sabha and forms the central government, led by the Prime Minister.
E103330 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: ruling party (India) | Statement: [Opposition (India), relatedConcept, ruling party (India)]
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: ruling party (India)
Triple: [Opposition (India), relatedConcept, ruling party (India)]
Generated description
The ruling party in India is the political party or coalition that holds a majority in the Lok Sabha and forms the central government, led by the Prime Minister.

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_69f76e9952b88190a6fe01ba01476520 completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69fb2fcdca94819082d3806d7bc6d5f0 completed May 6, 2026, 12:10 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3efdcac9488190aaf5adcdc5806f70 completed June 26, 2026, 10:31 p.m.
NEDg Description generation batch_6a3efedb154481909bc7a43a00ea2608 completed June 26, 2026, 10:36 p.m.
NED2 Entity disambiguation (via description) batch_6a3eff5a05688190bba19924a228dae9 completed June 26, 2026, 10:38 p.m.
Created at: May 3, 2026, 4:14 p.m.