Triple

T26894386
Position Surface form Disambiguated ID Type / Status
Subject Lasbela District E677860 entity
Predicate hasShipBreakingYard P126874 FINISHED
Object Gaddani ship-breaking yard
Gaddani ship-breaking yard is one of the world’s largest ship-breaking facilities, located on the Arabian Sea coast of Pakistan where decommissioned ships are dismantled for scrap.
 E1746725 NE FINISHED

How this triple was built (3 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: Gaddani ship-breaking yard | Statement: [Lasbela District, hasShipBreakingYard, Gaddani ship-breaking yard]
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: Gaddani ship-breaking yard
Triple: [Lasbela District, hasShipBreakingYard, Gaddani ship-breaking yard]
Generated description
Gaddani ship-breaking yard is one of the world’s largest ship-breaking facilities, located on the Arabian Sea coast of Pakistan where decommissioned ships are dismantled for scrap.
PD Predicate disambiguation gpt-5-mini-2025-08-07 
Target predicate: hasShipBreakingYard
Context triple: [Lasbela District, hasShipBreakingYard, Gaddani ship-breaking yard]
  • A. shipBreakingHub chosen
    Indicates that a location serves as a central site where ships are dismantled or broken down, typically for recycling or scrap.
  • B. shipyardLocatedOn
    Indicates that a shipyard is situated on or within the geographic area of a specified landmass, coastline, or body of water.
  • C. hasShipyardType
    Indicates the specific category or classification of shipyard associated with an entity.
  • D. hasShipRig
    Indicates that an entity is equipped with, or characterized by, a particular type of ship rigging configuration.
  • E. shipyard
    Indicates a relationship where a location functions as a facility for building, repairing, or maintaining ships.
  • F. None of above.

Provenance (6 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_69eee9befee48190a26f214faa867be7 completed April 27, 2026, 4:44 a.m.
NER Named-entity recognition batch_69f6691f5e188190b12c7b2eb729a45e completed May 2, 2026, 9:14 p.m.
NED1 Entity disambiguation (via context triple) batch_6a121ea2fa008190913b10dedb3b67a6 completed May 23, 2026, 9:39 p.m.
NEDg Description generation batch_6a121f90eec08190bd18be556349e464 completed May 23, 2026, 9:43 p.m.
NED2 Entity disambiguation (via description) batch_6a12205e89f4819098a8901d520e9c7d completed May 23, 2026, 9:47 p.m.
PD Predicate disambiguation batch_69f66598d6008190a7ca8ff80399fd34 completed May 2, 2026, 8:59 p.m.
Created at: April 27, 2026, 5:47 a.m.