Triple
T33593520
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oliver Lacon |
E860494
|
entity |
| Predicate | fictionalCountryOfService |
P197244
|
FINISHED |
| Object | United Kingdom |
—
|
NE NERFINISHED |
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: United Kingdom | Statement: [Oliver Lacon, fictionalCountryOfService, United Kingdom]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fictionalCountryOfService Context triple: [Oliver Lacon, fictionalCountryOfService, United Kingdom]
-
A.
fictionalServiceBranch
Indicates that an entity is associated with a military or organizational service branch that exists only within a fictional or imaginary context.
-
B.
countryOfMilitaryService
Indicates that an entity served or is serving in the armed forces of a specified country.
-
C.
fictionalCountryMentioned
Indicates that a fictional or imaginary country is referenced or discussed in relation to an entity.
-
D.
fictionalCountryLocation
Indicates that a fictional country is located within, or geographically associated with, a specified place or region.
-
E.
placeOfMilitaryService
Indicates the location or institution where a person performed their military service.
- F. None of above. chosen
Provenance (4 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_69f3497e70e48190951c94d072879bec |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69fe7eb4b8348190bb19d35766189ed4 |
completed | May 9, 2026, 12:24 a.m. |
| PD | Predicate disambiguation | batch_69fe7c35d2148190ab952e54feda1e76 |
completed | May 9, 2026, 12:13 a.m. |
| PDg | Predicate description generation | batch_69fe7eb31b04819081be531fd9f8a78c |
completed | May 9, 2026, 12:24 a.m. |
Created at: May 1, 2026, 1:41 a.m.