Triple

T2482849
Position Surface form Disambiguated ID Type / Status
Subject Hazara Division E55858 entity
Predicate containsSettlement P847 FINISHED
Object Abbottabad E54836 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: Abbottabad | Statement: [Hazara Division, containsSettlement, Abbottabad]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Abbottabad
Context triple: [Hazara Division, containsSettlement, Abbottabad]
  • A. Abbottabad chosen
    Abbottabad is a city in northern Pakistan known for its military academy, scenic hilly landscape, and role as a major urban center in the Khyber Pakhtunkhwa province.
  • B. Peshawar
    Peshawar is one of Pakistan’s oldest and largest cities, a historic cultural and economic hub located near the Khyber Pass in the country’s northwest.
  • C. Quetta
    Quetta is a major city in western Pakistan known as the provincial capital of Balochistan and a key commercial and military center near the Afghan border.
  • D. Rawalpindi
    Rawalpindi is a major city in Pakistan’s Punjab province, historically significant as a former temporary national capital and now a key commercial and military center.
  • E. Kandahar
    Kandahar is a historic city in southern Afghanistan that has long served as a major political, cultural, and commercial center in the region.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69ab49e670a88190b928e08302381710 completed March 6, 2026, 9:40 p.m.
NER Named-entity recognition batch_69abd163378481908b75f2f5de0e89c6 completed March 7, 2026, 7:18 a.m.
NED1 Entity disambiguation (via context triple) batch_69af5ce10c848190af545b82f994e459 completed March 9, 2026, 11:50 p.m.
Created at: March 6, 2026, 9:45 p.m.