Triple
T175189
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ANZUS |
E3557
|
entity |
| Predicate | hasMeetingType |
P3082
|
FINISHED |
| Object | ministerial consultations |
—
|
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: ministerial consultations | Statement: [ANZUS, hasMeetingType, ministerial consultations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMeetingType Context triple: [ANZUS, hasMeetingType, ministerial consultations]
-
A.
meetingType
chosen
Indicates the specific category or format of a meeting that characterizes how it is organized or conducted.
-
B.
hasConference
Indicates that an entity organizes, hosts, or is associated with a specific conference.
-
C.
meetsAs
Indicates that two entities encounter or come together at the same place and time, typically in a planned or recognized interaction.
-
D.
meetsEvery
Indicates that one entity encounters or comes into contact with every member of a specified set of entities.
-
E.
hasMemberType
Indicates that an entity includes or is associated with members belonging to a specified type or category.
- 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_69a25374990081909766d30c79a18e0e |
completed | Feb. 28, 2026, 2:31 a.m. |
| NER | Named-entity recognition | batch_69a258e32da88190ad9485aecd0bf08f |
completed | Feb. 28, 2026, 2:54 a.m. |
| PD | Predicate disambiguation | batch_69a25669d99481908c5e82ba8641205a |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:39 a.m.