Triple
T4371588
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | William Lyon Mackenzie King |
E98908
|
entity |
| Predicate | totalTimeInOffice |
P19680
|
FINISHED |
| Object | more than 21 years |
—
|
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: more than 21 years | Statement: [William Lyon Mackenzie King, totalTimeInOffice, more than 21 years]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: totalTimeInOffice Context triple: [William Lyon Mackenzie King, totalTimeInOffice, more than 21 years]
-
A.
inOfficeDuring
Indicates that an entity holds or occupies an office or position throughout a specified time period.
-
B.
spentTimeIn
Indicates that an entity has spent a certain amount or period of time in a particular place or context.
-
C.
occupationDuration
chosen
Indicates the length of time an entity holds or has held a particular occupation or role.
-
D.
fieldOfficePresence
Indicates that an entity maintains a physical field office or on-the-ground operational presence in a particular location or jurisdiction.
-
E.
controlledOffice
Indicates that one entity has authority over, manages, or directs the operations of a particular office or administrative location.
- 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_69b3454db3708190aeafd814413c4c3d |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3521dffbc8190b9300a7f4f64bdc0 |
completed | March 12, 2026, 11:54 p.m. |
| PD | Predicate disambiguation | batch_69b34f53e3cc8190bf5d4dbe2413bf65 |
completed | March 12, 2026, 11:42 p.m. |
Created at: March 12, 2026, 11:17 p.m.