Triple

T27224756
Position Surface form Disambiguated ID Type / Status
Subject Periya Kovil E681378 entity
Predicate alsoKnownAs P39 FINISHED
Object Srirangam Temple
Srirangam Temple is a vast and ancient Hindu temple complex in Tamil Nadu, India, renowned as one of the most important pilgrimage centers dedicated to Lord Ranganatha (Vishnu).
E1945836 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: Srirangam Temple | Statement: [Periya Kovil, alsoKnownAs, Srirangam Temple]
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: Srirangam Temple
Triple: [Periya Kovil, alsoKnownAs, Srirangam Temple]
Generated description
Srirangam Temple is a vast and ancient Hindu temple complex in Tamil Nadu, India, renowned as one of the most important pilgrimage centers dedicated to Lord Ranganatha (Vishnu).

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_69eefac9f64c8190a07490fe0c8b72a3 completed April 27, 2026, 5:57 a.m.
NER Named-entity recognition batch_69f6264a03648190a9b6904ce2f7aeeb completed May 2, 2026, 4:28 p.m.
NED1 Entity disambiguation (via context triple) batch_6a292ae605148190936d8e9762c6d2f6 completed June 10, 2026, 9:14 a.m.
NEDg Description generation batch_6a292f17b0d88190a8127db7fef88d4a completed June 10, 2026, 9:32 a.m.
NED2 Entity disambiguation (via description) batch_6a29336ad4a88190913d094aaa393fcf completed June 10, 2026, 9:50 a.m.
Created at: April 27, 2026, 9:44 a.m.