Triple

T28712200
Position Surface form Disambiguated ID Type / Status
Subject Jagjit Singh E729858 entity
Predicate educatedAt P5 FINISHED
Object Khalsa College, Sri Ganganagar
Khalsa College, Sri Ganganagar is a higher education institution in Sri Ganganagar, Rajasthan, known for offering undergraduate and postgraduate programs across various disciplines.
E1830566 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: Khalsa College, Sri Ganganagar | Statement: [Jagjit Singh, educatedAt, Khalsa College, Sri Ganganagar]
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: Khalsa College, Sri Ganganagar
Triple: [Jagjit Singh, educatedAt, Khalsa College, Sri Ganganagar]
Generated description
Khalsa College, Sri Ganganagar is a higher education institution in Sri Ganganagar, Rajasthan, known for offering undergraduate and postgraduate programs across various disciplines.

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_69f043e7d5a4819094b18aca10b1e024 completed April 28, 2026, 5:21 a.m.
NER Named-entity recognition batch_69f656d92c088190918720a02e2d923c completed May 2, 2026, 7:56 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1ccf542a848190a044c22a54e9c5ee completed June 1, 2026, 12:16 a.m.
NEDg Description generation batch_6a1ccff9242081908a415b1d68855a63 completed June 1, 2026, 12:19 a.m.
NED2 Entity disambiguation (via description) batch_6a249466d5b08190bd3886ef517cb367 completed June 6, 2026, 9:43 p.m.
Created at: April 28, 2026, 5:48 a.m.