Triple

T12754219
Position Surface form Disambiguated ID Type / Status
Subject Narowal E304814 entity
Predicate hasNearbyTown P3883 FINISHED
Object Shakargarh
Shakargarh is a town in Punjab, Pakistan, known for its agricultural surroundings and proximity to the border with India.
E1019961 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: Shakargarh | Statement: [Narowal, hasNearbyTown, Shakargarh]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Shakargarh
Context triple: [Narowal, hasNearbyTown, Shakargarh]
  • A. Kheragarh
    Kheragarh is a town in the culturally significant Braj region of northern India, known for its historical and religious associations with the broader Mathura–Agra area.
  • B. Kharbanda
    Kharbanda is the birth name of Öljeitü, the Ilkhanid ruler of Persia in the early 14th century.
  • C. Kishtwari
    Kishtwari is an Indo-Aryan language spoken primarily in the Kishtwar region of Jammu and Kashmir, India.
  • D. Arjan Garh
    Arjan Garh is an elevated station on the Delhi Metro network serving the southern outskirts of Delhi near the Haryana border.
  • E. Bhit Shah
    Bhit Shah is a town in Sindh, Pakistan, renowned as a spiritual and cultural center built around the shrine of the revered Sufi poet Shah Abdul Latif Bhittai.
  • 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: Shakargarh
Triple: [Narowal, hasNearbyTown, Shakargarh]
Generated description
Shakargarh is a town in Punjab, Pakistan, known for its agricultural surroundings and proximity to the border with India.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Shakargarh
Target entity description: Shakargarh is a town in Punjab, Pakistan, known for its agricultural surroundings and proximity to the border with India.
  • A. Kheragarh
    Kheragarh is a town in the culturally significant Braj region of northern India, known for its historical and religious associations with the broader Mathura–Agra area.
  • B. Kharbanda
    Kharbanda is the birth name of Öljeitü, the Ilkhanid ruler of Persia in the early 14th century.
  • C. Kishtwari
    Kishtwari is an Indo-Aryan language spoken primarily in the Kishtwar region of Jammu and Kashmir, India.
  • D. Arjan Garh
    Arjan Garh is an elevated station on the Delhi Metro network serving the southern outskirts of Delhi near the Haryana border.
  • E. Bhit Shah
    Bhit Shah is a town in Sindh, Pakistan, renowned as a spiritual and cultural center built around the shrine of the revered Sufi poet Shah Abdul Latif Bhittai.
  • 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_69d7bdf1fcd081909ffb0e0d6fa3a07d completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d96d89ea70819098c470344f172167 completed April 10, 2026, 9:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6d5eba3b0819089da65be31f3d0e6 completed May 3, 2026, 4:58 a.m.
NEDg Description generation batch_69f6da15c2cc8190897e00a64e20e6b9 completed May 3, 2026, 5:16 a.m.
NED2 Entity disambiguation (via description) batch_69f6daa21ff88190af9b7ffb7cbb2b21 completed May 3, 2026, 5:18 a.m.
Created at: April 9, 2026, 5:27 p.m.