Triple
T19887911
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Vereker, 8th Viscount Gort |
E477949
|
entity |
| Predicate | hasMilitaryCareerStart |
P19194
|
FINISHED |
| Object | early 20th century |
—
|
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: early 20th century | Statement: [John Vereker, 8th Viscount Gort, hasMilitaryCareerStart, early 20th century]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMilitaryCareerStart Context triple: [John Vereker, 8th Viscount Gort, hasMilitaryCareerStart, early 20th century]
-
A.
hasMilitaryServiceStart
chosen
Indicates the date or point in time when an entity’s period of military service began.
-
B.
hadMilitaryServiceFrom
Indicates that an entity performed or was engaged in military service starting from a specified point in time.
-
C.
hasMilitaryBranch
Indicates that an entity is associated with, served in, or is part of a specific branch of a military organization.
-
D.
militaryBackground
Indicates that an entity has prior or current experience, service, or training in a military organization.
-
E.
hadMilitaryPost
Indicates that an entity held an official position or assignment within a military 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_69d8e51f32b08190b3687f4f60353250 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e6590b12c08190bf44a3f3b2cb9122 |
completed | April 20, 2026, 4:49 p.m. |
| PD | Predicate disambiguation | batch_69e537e8c4e481909fe95d795b4864e7 |
completed | April 19, 2026, 8:15 p.m. |
Created at: April 10, 2026, 1:52 p.m.