Triple
T5044946
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Antoinette Avril Gardiner |
E113638
|
entity |
| Predicate | militaryConnection |
P22805
|
FINISHED |
| Object | grew up in a British military family |
—
|
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: grew up in a British military family | Statement: [Antoinette Avril Gardiner, militaryConnection, grew up in a British military family]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: militaryConnection Context triple: [Antoinette Avril Gardiner, militaryConnection, grew up in a British military family]
-
A.
hasMilitaryAssociation
chosen
Indicates a relationship in which an entity is connected or affiliated with a military organization, activity, or function.
-
B.
militaryBranchEligibility
Indicates that an entity meets the required conditions to serve in a specified branch of the military.
-
C.
militaryBackground
Indicates that an entity has prior or current experience, service, or training in a military organization.
-
D.
hasMilitaryBranch
Indicates that an entity is associated with, served in, or is part of a specific branch of a military organization.
-
E.
militaryStatus
Indicates the relationship between an entity and a military organization in terms of service condition, such as active duty, reserve, veteran, or non-military status.
- 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_69bd44391fc48190a311ce9c826c209b |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd73fd81788190b7799f519277119a |
completed | March 20, 2026, 4:21 p.m. |
| PD | Predicate disambiguation | batch_69bd71529d608190a53470ba6c14bb1d |
completed | March 20, 2026, 4:09 p.m. |
Created at: March 20, 2026, 1:37 p.m.