Triple
T38604510
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Truss ministry |
E934304
|
entity |
| Predicate | timeInOfficeCharacterisation |
P87233
|
FINISHED |
| Object | short-lived |
—
|
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: short-lived | Statement: [Truss ministry, timeInOfficeCharacterisation, short-lived]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: timeInOfficeCharacterisation Context triple: [Truss ministry, timeInOfficeCharacterisation, short-lived]
-
A.
timeInOfficeCharacteristic
chosen
Indicates a characteristic or attribute specifically related to the duration or period an entity spends in office or in a particular official role.
-
B.
timeInOfficeRelation
Indicates a temporal relationship specifying the duration or period that an entity holds or held a particular office or position.
-
C.
chronologyWithinOffice
Indicates that one event or action occurs within the temporal span of another event or action associated with the same office or term of office.
-
D.
timeInOfficeBeginsIn
Indicates the point in time or date when an entity’s term, tenure, or period in office starts.
-
E.
periodOfKeyPoliticalRole
Indicates the time span during which an entity held a particular key political role or office.
- 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_69fcdb0de8c08190928cd1323f80ab5c |
completed | May 7, 2026, 6:33 p.m. |
| PD | Predicate disambiguation | batch_69fcd9017dd88190b32a73fe78909740 |
completed | May 7, 2026, 6:25 p.m. |
Created at: May 3, 2026, 4:32 p.m.