Triple
T9684661
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yawuru people |
E234374
|
entity |
| Predicate | agreementArea |
P53993
|
FINISHED |
| Object | Broome township and surrounds |
—
|
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: Broome township and surrounds | Statement: [Yawuru people, agreementArea, Broome township and surrounds]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: agreementArea Context triple: [Yawuru people, agreementArea, Broome township and surrounds]
-
A.
agreement
Indicates that two or more parties mutually consent to and accept shared terms, conditions, or understandings.
-
B.
treatyArea
chosen
Indicates the geographic region or jurisdiction to which a treaty or formal agreement applies.
-
C.
area
Indicates that one entity has a measured two-dimensional extent or surface size quantified by another entity.
-
D.
aimOfAgreement
Indicates the intended purpose or objective that an agreement is designed to achieve.
-
E.
legalArea
Indicates the specific field or branch of law that a legal matter, case, or document pertains to.
- 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_69ca84ca73208190957a900c8543bdcc |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cd9cd0877c81909fde1989d946aae9 |
completed | April 1, 2026, 10:31 p.m. |
| PD | Predicate disambiguation | batch_69ccd5b840f081909f66bf0b66d17d9b |
completed | April 1, 2026, 8:22 a.m. |
Created at: March 30, 2026, 8:16 p.m.