Triple
T38212349
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kyaukphyu Township |
E1010582
|
entity |
| Predicate | hasPlannedProjectPartner |
P141436
|
FINISHED |
| Object | China |
—
|
NE NERFINISHED |
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: China | Statement: [Kyaukphyu Township, hasPlannedProjectPartner, China]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPlannedProjectPartner Context triple: [Kyaukphyu Township, hasPlannedProjectPartner, China]
-
A.
hasPartnerInWork
Indicates that one entity collaborates professionally or is partnered with another entity in a work-related context.
-
B.
hasPartner
Indicates that one entity is in a partner relationship (such as romantic, life, or business partnership) with another entity.
-
C.
hasPartnerOrganization
Indicates that an entity is formally associated or collaborates with another entity as a partner organization.
-
D.
partnerInBusinessOrProjects
chosen
Indicates that two entities collaborate as partners in a business venture or joint project, sharing responsibilities, risks, and/or benefits.
-
E.
hasExternalPartner
Indicates that an entity is engaged in a relationship, collaboration, or interaction with a partner organization or individual outside its own structure or system.
- 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_69f76dcdc7708190a5f1751d53f40ffe |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fe766490c081908c49c8cc07d0ae9b |
completed | May 8, 2026, 11:48 p.m. |
| PD | Predicate disambiguation | batch_69fe75bb5f4481908572a5ffcbdc5154 |
completed | May 8, 2026, 11:46 p.m. |
Created at: May 3, 2026, 4:30 p.m.