Triple

T3796537
Position Surface form Disambiguated ID Type / Status
Subject Hisar district E89782 entity
Predicate hasMajorTown P316 FINISHED
Object Hansi
Hansi is a historic town in the Hisar district of Haryana, India, known for its ancient forts and archaeological significance.
 E389633 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: Hansi | Statement: [Hisar district, hasMajorTown, Hansi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Hansi
Context triple: [Hisar district, hasMajorTown, Hansi]
  • A. Hans
    Hans is a masculine given name of Germanic origin commonly used in Germanic and Scandinavian countries.
  • B. Günther
    Günther is a German masculine given name traditionally associated with figures of Germanic origin and culture.
  • C. Hermann
    Hermann Minkowski was a German mathematician best known for developing the geometric formulation of special relativity using four-dimensional spacetime.
  • D. Hermann
    Hermann is a German surname borne by various notable individuals across fields such as philosophy, science, and the arts.
  • E. Helmut
    Helmut is a masculine given name of German origin, historically common in German-speaking countries.
  • 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: Hansi
Triple: [Hisar district, hasMajorTown, Hansi]
Generated description
Hansi is a historic town in the Hisar district of Haryana, India, known for its ancient forts and archaeological significance.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Hansi
Target entity description: Hansi is a historic town in the Hisar district of Haryana, India, known for its ancient forts and archaeological significance.
  • A. Hans
    Hans is a masculine given name of Germanic origin commonly used in Germanic and Scandinavian countries.
  • B. Günther
    Günther is a German masculine given name traditionally associated with figures of Germanic origin and culture.
  • C. Hermann
    Hermann Minkowski was a German mathematician best known for developing the geometric formulation of special relativity using four-dimensional spacetime.
  • D. Hermann
    Hermann is a German surname borne by various notable individuals across fields such as philosophy, science, and the arts.
  • E. Helmut
    Helmut is a masculine given name of German origin, historically common in German-speaking countries.
  • 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_69aed9597d6881909b6ee3b9de859223 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aee79f09bc8190b7514a11a030eba5 completed March 9, 2026, 3:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4f05ea5e081908c4714ca35aed48b completed March 14, 2026, 5:21 a.m.
NEDg Description generation batch_69b4f2ed663c8190be431c7aae60259e completed March 14, 2026, 5:32 a.m.
NED2 Entity disambiguation (via description) batch_69b4f72eba988190acb96b44fc8b7c30 completed March 14, 2026, 5:50 a.m.
Created at: March 9, 2026, 3:15 p.m.