Triple

T9620833
Position Surface form Disambiguated ID Type / Status
Subject Trans-Karakoram Tract E232335 entity
Predicate legalStatusAccordingToIndia P89300 FINISHED
Object illegally ceded by Pakistan to China LITERAL 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: illegally ceded by Pakistan to China | Statement: [Trans-Karakoram Tract, legalStatusAccordingToIndia, illegally ceded by Pakistan to China]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: legalStatusAccordingToIndia
Context triple: [Trans-Karakoram Tract, legalStatusAccordingToIndia, illegally ceded by Pakistan to China]
  • A. legalStatusVariesBy
    Indicates that the legal status of something differs depending on a specified jurisdiction, context, or set of conditions.
  • B. legalStatusAtIssue
    Indicates that the legal status of an entity is the central subject of dispute, consideration, or determination in a legal context.
  • C. legalStatusInManyCountries
    Indicates that the subject has a particular legal classification or standing that is recognized across numerous countries.
  • D. hasLegalStatus
    Indicates that an entity possesses a particular legal classification, recognition, or standing under law.
  • E. legalStatusInChina
    Indicates the legal status or standing that an entity holds under the laws and regulations of China.
  • F. None of above. chosen

Provenance (4 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_69ca84867bb88190b4b57dd5a56d5691 completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd9ad3a8d88190b1414aa676d82f36 completed April 1, 2026, 10:23 p.m.
PD Predicate disambiguation batch_69ccd5aa1d2c8190a287bf1cf4a3037e completed April 1, 2026, 8:22 a.m.
PDg Predicate description generation batch_69ccd93fc45c8190a823305e461e581d completed April 1, 2026, 8:37 a.m.
Created at: March 30, 2026, 8:09 p.m.