Triple
T29554208
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Australia and Indonesia |
E749860
|
entity |
| Predicate | haveConsulatesOfIndonesiaIn |
P167449
|
FINISHED |
| Object | Sydney |
—
|
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: Sydney | Statement: [Australia and Indonesia, haveConsulatesOfIndonesiaIn, Sydney]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: haveConsulatesOfIndonesiaIn Context triple: [Australia and Indonesia, haveConsulatesOfIndonesiaIn, Sydney]
-
A.
haveConsulates
Indicates that one country maintains consular offices or consulates within the territory of another country.
-
B.
haveConsulatesOfAustraliaIn
Indicates that one location hosts consular offices representing Australia within its territory.
-
C.
hasConsulateOfUnitedStatesIn
Indicates that a consulate of the United States is located in the specified place.
-
D.
overseesIndianConsulatesIn
Indicates that an entity has administrative authority or supervisory responsibility over Indian consulates located in a specified place or jurisdiction.
-
E.
hasDiplomaticStaffFrom
Indicates that an entity has diplomatic personnel who originate from or represent another specified entity.
- 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_69f0bd4919e48190942b2a13d5b97d03 |
completed | April 28, 2026, 1:59 p.m. |
| NER | Named-entity recognition | batch_69f66cf946f881909d177507a28a657b |
completed | May 2, 2026, 9:30 p.m. |
| PD | Predicate disambiguation | batch_69f6659d36208190b01412600a4ed57d |
completed | May 2, 2026, 8:59 p.m. |
| PDg | Predicate description generation | batch_69f6691da93081909deaf680614fc900 |
completed | May 2, 2026, 9:14 p.m. |
Created at: April 28, 2026, 5:14 p.m.