Triple

T12828943
Position Surface form Disambiguated ID Type / Status
Subject Saddar commercial area E306733 entity
Predicate hasLandmark P105 FINISHED
Object Zaibunnisa Street E1005709 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: Zaibunnisa Street | Statement: [Saddar commercial area, hasLandmark, Zaibunnisa Street]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Zaibunnisa Street
Context triple: [Saddar commercial area, hasLandmark, Zaibunnisa Street]
  • A. Zaib-un-Nisa Street chosen
    Zaib-un-Nisa Street is a prominent commercial and shopping street located in the Saddar area of Karachi, Pakistan.
  • B. Javad Khan Street
    Javad Khan Street is a central thoroughfare and popular pedestrian area in Ganja, Azerbaijan, known for its shops, cafes, and historical atmosphere.
  • C. Shah Baig Lane
    Shah Baig Lane is a residential neighborhood located within Lyari Town in Karachi, Pakistan.
  • D. Ghuznee Street
    Ghuznee Street is a central Wellington, New Zealand thoroughfare known for connecting key inner-city areas and lying close to the popular Cuba Street precinct.
  • E. Allama Rasheed Turabi Road
    Allama Rasheed Turabi Road is a key thoroughfare in Karachi, Pakistan, serving as an important connector within the Federal B Area residential and commercial district.
  • 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_69d7bdf52b94819096d6f0ba4ab50a98 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d96faf9ae481908265e198f917d1e6 completed April 10, 2026, 9:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6a5466d988190ae0df2f4058287a1 completed May 3, 2026, 1:30 a.m.
Created at: April 9, 2026, 5:34 p.m.