Triple
T10110599
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | People’s Armed Police |
E218228
|
entity |
| Predicate | shortName |
P43
|
FINISHED |
| Object | PAP |
E218228
|
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: PAP | Statement: [People’s Armed Police, shortName, PAP]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: PAP Context triple: [People’s Armed Police, shortName, PAP]
-
A.
PAP
PAP is the legislative body of the African Union that aims to promote democracy, human rights, and integration across African states.
-
B.
PAP
chosen
PAP is the commonly used abbreviation for China’s paramilitary People’s Armed Police force responsible for internal security and law enforcement support.
-
C.
PAP
PAP is the IATA airport code for Toussaint Louverture International Airport, the main international gateway serving Port-au-Prince, Haiti.
-
D.
PAPPG
PAPPG is the National Science Foundation’s comprehensive guide outlining the policies, procedures, and requirements for preparing and managing NSF grant proposals and awards.
-
E.
PAD
PAD is the three-letter National Rail station code for London Paddington, a major railway terminus in central London.
- 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_69ca83da93fc8190b54e44bc2b34857c |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cdd0cf39908190bba679ace095eefc |
completed | April 2, 2026, 2:13 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d2cc1805d08190bc39aadf1e84a569 |
completed | April 5, 2026, 8:54 p.m. |
Created at: March 30, 2026, 9:03 p.m.