Triple

T38030720
Position Surface form Disambiguated ID Type / Status
Subject Taj E948898 entity
Predicate hasSubBrand P6092 FINISHED
Object Taj Safaris
Taj Safaris is a luxury wildlife and safari lodge brand offering high-end nature and jungle experiences, primarily in India’s premier national parks.
E2254234 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: Taj Safaris | Statement: [Taj, hasSubBrand, Taj Safaris]
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: Taj Safaris
Triple: [Taj, hasSubBrand, Taj Safaris]
Generated description
Taj Safaris is a luxury wildlife and safari lodge brand offering high-end nature and jungle experiences, primarily in India’s premier national parks.

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_69f76efd1bc48190a729097fe5177b61 completed May 3, 2026, 3:51 p.m.
NER Named-entity recognition batch_69fbc999ba0081908ec76b8a771bf071 completed May 6, 2026, 11:07 p.m.
NED1 Entity disambiguation (via context triple) batch_6a415d2c749c8190a820541b3ea2203e completed June 28, 2026, 5:43 p.m.
NEDg Description generation batch_6a415de6354c8190b728481c8b9b7544 completed June 28, 2026, 5:46 p.m.
NED2 Entity disambiguation (via description) batch_6a415f54846081909b862a6d8c2cc73a completed June 28, 2026, 5:52 p.m.
Created at: May 3, 2026, 4:20 p.m.