Triple

T27240195
Position Surface form Disambiguated ID Type / Status
Subject The Light of Asia E687184 entity
Predicate director P255 FINISHED
Object Himansu Rai
Himansu Rai was an influential early Indian film producer, director, and actor best known for his pioneering work in Indo-European co-productions during the silent and early sound eras.
E1796331 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: Himansu Rai | Statement: [The Light of Asia, director, Himansu Rai]
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: Himansu Rai
Triple: [The Light of Asia, director, Himansu Rai]
Generated description
Himansu Rai was an influential early Indian film producer, director, and actor best known for his pioneering work in Indo-European co-productions during the silent and early sound eras.

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_69ef355547408190b5ca0d777c65040a completed April 27, 2026, 10:07 a.m.
NER Named-entity recognition batch_69f6267d1440819095cd651478334377 completed May 2, 2026, 4:29 p.m.
NED1 Entity disambiguation (via context triple) batch_6a13112a5fac81908580666ea37948ca completed May 24, 2026, 2:54 p.m.
NEDg Description generation batch_6a13128cd3ac8190bccb59b734bab1bd completed May 24, 2026, 3 p.m.
NED2 Entity disambiguation (via description) batch_6a1314611fac81909731effc36b3a00b completed May 24, 2026, 3:08 p.m.
Created at: April 27, 2026, 10:37 a.m.