Triple
T38604345
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Minister for COVID Vaccine Deployment |
E934301
|
entity |
| Predicate | startTimeOfFirstOfficeholder |
P38523
|
FINISHED |
| Object | November 2020 |
—
|
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: November 2020 | Statement: [Minister for COVID Vaccine Deployment, startTimeOfFirstOfficeholder, November 2020]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: startTimeOfFirstOfficeholder Context triple: [Minister for COVID Vaccine Deployment, startTimeOfFirstOfficeholder, November 2020]
-
A.
officeHolderStartTime
Indicates the date and time at which an individual begins holding a particular office or position.
-
B.
firstOfficeHolderStart
chosen
Indicates the date or time when the first person to hold a particular office or position began their term.
-
C.
previousOfficeHolderStartTime
Indicates the date and time when the immediately preceding office holder first began their term in that office.
-
D.
lastOfficeHolderStartDate
Indicates the date on which the most recent person to hold a particular office or position began their term.
-
E.
significantOfficeHolderStartTime
Indicates the date and time at which an entity begins holding a significant office or position.
- 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_69f76ecc17688190b389b693a5927501 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_6a01839b071481909f9cc79a6a09387d |
completed | May 11, 2026, 7:22 a.m. |
| PD | Predicate disambiguation | batch_6a017edbed688190baa61cbae5110c8e |
completed | May 11, 2026, 7:01 a.m. |
Created at: May 3, 2026, 4:32 p.m.