Triple

T29657682
Position Surface form Disambiguated ID Type / Status
Subject Bum La Pass E750313 entity
Predicate borderMeetingPoint P195900 FINISHED
Object Indo-China Border Personnel Meetings
Indo-China Border Personnel Meetings are regular military-to-military interactions between Indian and Chinese border forces aimed at maintaining peace, resolving local issues, and building confidence along the Line of Actual Control.
 E810183 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: Indo-China Border Personnel Meetings | Statement: [Bum La Pass, borderMeetingPoint, Indo-China Border Personnel Meetings]
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: Indo-China Border Personnel Meetings
Triple: [Bum La Pass, borderMeetingPoint, Indo-China Border Personnel Meetings]
Generated description
Indo-China Border Personnel Meetings are regular military-to-military interactions between Indian and Chinese border forces aimed at maintaining peace, resolving local issues, and building confidence along the Line of Actual Control.
PD Predicate disambiguation gpt-5-mini-2025-08-07 
Target predicate: borderMeetingPoint
Context triple: [Bum La Pass, borderMeetingPoint, Indo-China Border Personnel Meetings]
  • A. borderPoint
    Indicates a point that lies on the boundary between two regions or entities.
  • B. borderStationFor
    Indicates that a particular border station serves, monitors, or is responsible for a specific border crossing or boundary segment.
  • C. borderStation
    Indicates a facility or checkpoint located at or near a border where cross-boundary movement, control, or processing of people or goods occurs.
  • D. borderTerminus
    Indicates the endpoint location where a border between two areas or entities begins or ends.
  • E. borderPass
    Indicates that one entity crosses or moves through the boundary separating two regions or jurisdictions.
  • F. None of above. chosen

Provenance (7 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_69f0d6226fe881908819197c9ef9ee04 completed April 28, 2026, 3:45 p.m.
NER Named-entity recognition batch_69fdee770af48190aca2670db50f8b49 completed May 8, 2026, 2:08 p.m.
NED1 Entity disambiguation (via context triple) batch_6a26618b7fe881909c2bb6681ef65217 completed June 8, 2026, 6:30 a.m.
NEDg Description generation batch_6a26656b2d208190aeda49d3fdadd561 completed June 8, 2026, 6:47 a.m.
NED2 Entity disambiguation (via description) batch_6a266abade508190ad7a5d6c034cc354 completed June 8, 2026, 7:09 a.m.
PD Predicate disambiguation batch_69fdecec98a08190a357d816dc2a6dbe completed May 8, 2026, 2:02 p.m.
PDg Predicate description generation batch_69fdee75d1408190bba58a9cef200a54 completed May 8, 2026, 2:08 p.m.
Created at: April 28, 2026, 6:56 p.m.