Triple
T19102042
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shipki La Indo–China trade point |
E467556
|
entity |
| Predicate | hasImmigrationCheckPost |
P7852
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Shipki La Indo–China trade point, hasImmigrationCheckPost, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasImmigrationCheckPost Context triple: [Shipki La Indo–China trade point, hasImmigrationCheckPost, yes]
-
A.
hasCustomsAndImmigration
chosen
Indicates that customs and immigration control services are present or provided at a given location or facility.
-
B.
hasCustomsCheckpoint
Indicates that a location or route includes an official customs inspection point where goods, vehicles, or people are checked for compliance with border regulations.
-
C.
hasBorderPostWith
Indicates that two regions or territories share a border where an official border post or checkpoint is located between them.
-
D.
hasBorderControlStatus
Indicates the type or condition of border control that applies to a given entity or location.
-
E.
hasBorderControlIssues
Indicates that there are problems, weaknesses, or irregularities in the enforcement or management of border controls between entities.
- F. None of above.
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_69d8dd05ac4c8190b1967d8f97f3fb2f |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5e36e9bfc8190bbaccab169394d99 |
completed | April 20, 2026, 8:27 a.m. |
| PD | Predicate disambiguation | batch_69e4b9ac41848190afd0f33b42cebe99 |
completed | April 19, 2026, 11:17 a.m. |
Created at: April 10, 2026, 12:04 p.m.