Triple
T598809
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Queen of Papua New Guinea |
E11446
|
entity |
| Predicate | officeStatusAfter2022 |
P13710
|
FINISHED |
| Object | held by a king rather than a queen |
—
|
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: held by a king rather than a queen | Statement: [Queen of Papua New Guinea, officeStatusAfter2022, held by a king rather than a queen]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: officeStatusAfter2022 Context triple: [Queen of Papua New Guinea, officeStatusAfter2022, held by a king rather than a queen]
-
A.
combinedOfficeExistedUntil
Indicates that a merged or joint office or position remained in existence up to a specified end time or date.
-
B.
officeReconstitutedIn
Indicates that an official position or office was re-established or newly formed within a specified location or jurisdiction.
-
C.
establishedOffice
Indicates that an entity created or set up an official office or place of operation.
-
D.
laterStatus
chosen
Indicates that one entity represents a subsequent or resulting status or condition of another entity in time.
-
E.
worksWithOffice
Indicates that an entity collaborates or is professionally associated with a particular office or office-based organization.
- 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_69a4932779b881908688590d59c71900 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49dc4f7d08190990f70b9b3af6ce5 |
completed | March 1, 2026, 8:12 p.m. |
| PD | Predicate disambiguation | batch_69a49cf59cd0819084e67981cb371e25 |
completed | March 1, 2026, 8:09 p.m. |
Created at: March 1, 2026, 7:35 p.m.