Triple

T27127551
Position Surface form Disambiguated ID Type / Status
Subject Kalpeni Atoll E681472 entity
Predicate hasIsland P970 FINISHED
Object Tilakkam Island
Tilakkam Island is a small inhabited island that forms part of the Kalpeni Atoll in the Lakshadweep archipelago of India.
E2296771 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: Tilakkam Island | Statement: [Kalpeni Atoll, hasIsland, Tilakkam Island]
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: Tilakkam Island
Triple: [Kalpeni Atoll, hasIsland, Tilakkam Island]
Generated description
Tilakkam Island is a small inhabited island that forms part of the Kalpeni Atoll in the Lakshadweep archipelago of India.

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_69eefacbcc2081909ebf00daa23f1981 completed April 27, 2026, 5:57 a.m.
NER Named-entity recognition batch_69f6244939ac819095ebde8d81e35fad completed May 2, 2026, 4:20 p.m.
NED1 Entity disambiguation (via context triple) batch_6a82b6ea65948190b6efd3785de1a89b completed Aug. 17, 2026, 7:23 a.m.
NEDg Description generation batch_6a82b73b6d148190bc6d3b02ed2a15ca completed Aug. 17, 2026, 7:24 a.m.
NED2 Entity disambiguation (via description) batch_6a82b78d72cc8190af064bc4d907fd6b completed Aug. 17, 2026, 7:26 a.m.
Created at: April 27, 2026, 9:02 a.m.