Triple

T29299296
Position Surface form Disambiguated ID Type / Status
Subject Singam E742916 entity
Predicate mainCharacter P1183 FINISHED
Object Durai Singam
Durai Singam is a fearless and principled police officer from the Tamil action film series "Singam," portrayed by actor Suriya.
E1921693 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: Durai Singam | Statement: [Singam, mainCharacter, Durai Singam]
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: Durai Singam
Triple: [Singam, mainCharacter, Durai Singam]
Generated description
Durai Singam is a fearless and principled police officer from the Tamil action film series "Singam," portrayed by actor Suriya.

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_69f09123ed9881909f351f7541933f5e completed April 28, 2026, 10:51 a.m.
NER Named-entity recognition batch_69f665a1a7148190ae6060514d16ffec completed May 2, 2026, 8:59 p.m.
NED1 Entity disambiguation (via context triple) batch_6a2856d1589081909f1fba2b402c33c4 completed June 9, 2026, 6:09 p.m.
NEDg Description generation batch_6a285983b18881909f6391f7e5dd45dd completed June 9, 2026, 6:20 p.m.
NED2 Entity disambiguation (via description) batch_6a285a1337088190a2fc8ab05a29fc2f completed June 9, 2026, 6:23 p.m.
Created at: April 28, 2026, 1:09 p.m.