Triple

T17549930
Position Surface form Disambiguated ID Type / Status
Subject Tiswadi taluka E427431 entity
Predicate contains P35 FINISHED
Object Merces
Merces is a village in the Tiswadi taluka of North Goa, India, known for its residential neighborhoods and proximity to the state capital, Panaji.
 E1274909 NE FINISHED

How this triple was built (4 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: Merces | Statement: [Tiswadi taluka, contains, Merces]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Merces
Context triple: [Tiswadi taluka, contains, Merces]
  • A. Mercedes
    Mercedes is a courageous and compassionate housekeeper who secretly aids the Spanish Maquis resistance in Guillermo del Toro’s dark fantasy film "Pan’s Labyrinth."
  • B. Mercedes
    Mercedes is a coastal municipality in the Philippine province of Camarines Norte known for its fishing industry and nearby island attractions.
  • C. Mercedes
    Mercedes is the given first name of the British former ballerina and television personality Darcey Bussell.
  • D. Mercedes
    Mercedes is a German Formula One team and automotive manufacturer renowned for its dominant performance in the early hybrid era of F1.
  • E. Mercedes
    Mercedes is a feminine given name of Spanish origin that became widely known through its association with the early automobile brand Mercedes-Benz.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
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: Merces
Triple: [Tiswadi taluka, contains, Merces]
Generated description
Merces is a village in the Tiswadi taluka of North Goa, India, known for its residential neighborhoods and proximity to the state capital, Panaji.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Merces
Target entity description: Merces is a village in the Tiswadi taluka of North Goa, India, known for its residential neighborhoods and proximity to the state capital, Panaji.
  • A. Mercedes
    Mercedes is a courageous and compassionate housekeeper who secretly aids the Spanish Maquis resistance in Guillermo del Toro’s dark fantasy film "Pan’s Labyrinth."
  • B. Mercedes
    Mercedes is a coastal municipality in the Philippine province of Camarines Norte known for its fishing industry and nearby island attractions.
  • C. Mercedes
    Mercedes is the given first name of the British former ballerina and television personality Darcey Bussell.
  • D. Mercedes
    Mercedes is a German Formula One team and automotive manufacturer renowned for its dominant performance in the early hybrid era of F1.
  • E. Mercedes
    Mercedes is a feminine given name of Spanish origin that became widely known through its association with the early automobile brand Mercedes-Benz.
  • F. None of above. chosen

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_69d889df6dc081908f67dbadc03c07ee completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e45463ddf88190a2c29f3246adcb6e completed April 19, 2026, 4:04 a.m.
NED1 Entity disambiguation (via context triple) batch_6a01d290edbc8190a7b2cb0835456890 completed May 11, 2026, 12:58 p.m.
NEDg Description generation batch_6a01d597c96c8190a5eca56a748da50c completed May 11, 2026, 1:11 p.m.
NED2 Entity disambiguation (via description) batch_6a01d639c220819088dd3389d1ab60ca completed May 11, 2026, 1:14 p.m.
Created at: April 10, 2026, 5:50 a.m.