Triple

T20871764
Position Surface form Disambiguated ID Type / Status
Subject Musa Qala District E513909 entity
Predicate provinceCapital P16248 FINISHED
Object Lashkargah NE NERFINISHED

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: Lashkargah | Statement: [Musa Qala District, provinceCapital, Lashkargah]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lashkargah
Context triple: [Musa Qala District, provinceCapital, Lashkargah]
  • A. Lashkargah chosen
    Lashkargah is a key urban and administrative center in southern Afghanistan, serving as the capital of Helmand Province and a strategic hub in the region.
  • B. Shahgarh
    Shahgarh is a town in the Sagar district of the central Indian state of Madhya Pradesh.
  • C. Pakdasht
    Pakdasht is a city in Tehran Province, Iran, known as an industrial and agricultural hub located southeast of Tehran.
  • D. Farashband
    Farashband is a small city in southern Iran known for its location within Fars Province and its surrounding agricultural and pastoral landscapes.
  • E. Shahdad
    Shahdad is an oasis town in Iran’s Kerman Province, known as a gateway to the Lut Desert (Dasht-e Lut) and its striking desert landscapes and kalut formations.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b4f675cc8190b4e745225b62eb66 completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6c4649cf88190b3ad946576aa46aa completed April 21, 2026, 12:27 a.m.
Created at: April 16, 2026, 12:45 p.m.