Triple

T28340499
Position Surface form Disambiguated ID Type / Status
Subject Tehsil Kallar Kahar E717795 entity
Predicate subdivisionOf P258 FINISHED
Object Province of Punjab
The Province of Punjab is Pakistan's most populous and agriculturally rich province, known for its fertile plains, major rivers, and role as the country's political and economic heartland.
E1823501 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: Province of Punjab | Statement: [Tehsil Kallar Kahar, subdivisionOf, Province of Punjab]
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: Province of Punjab
Triple: [Tehsil Kallar Kahar, subdivisionOf, Province of Punjab]
Generated description
The Province of Punjab is Pakistan's most populous and agriculturally rich province, known for its fertile plains, major rivers, and role as the country's political and economic heartland.

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_69eff6eb30388190b898b96c4be6f49d completed April 27, 2026, 11:53 p.m.
NER Named-entity recognition batch_69f64bd805f08190a6b503bf965ebbf5 completed May 2, 2026, 7:09 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1cac2e7d5c8190bbd84b7833a73216 completed May 31, 2026, 9:46 p.m.
NEDg Description generation batch_6a1cadadb2708190ab52e8a3df06eddb completed May 31, 2026, 9:52 p.m.
NED2 Entity disambiguation (via description) batch_6a1cae35e348819097647a4b59628818 completed May 31, 2026, 9:55 p.m.
Created at: April 28, 2026, 12:39 a.m.