Triple
T26754748
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Province of Moray |
E674639
|
entity |
| Predicate | territoryAbsorbedInto |
P32962
|
FINISHED |
| Object | royal sheriffdoms of Scotland |
—
|
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: royal sheriffdoms of Scotland | Statement: [Province of Moray, territoryAbsorbedInto, royal sheriffdoms of Scotland]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: territoryAbsorbedInto Context triple: [Province of Moray, territoryAbsorbedInto, royal sheriffdoms of Scotland]
-
A.
kingdomAnnexedBy
Indicates that a kingdom has been taken over and incorporated into another political entity through annexation.
-
B.
wasCoreTerritoryOf
Indicates that a region historically formed the central or most important territorial area belonging to a particular political or cultural entity.
-
C.
conqueredInPartBy
Indicates that one entity has gained control over a portion, but not the entirety, of another entity through conquest.
-
D.
annexedTerritory
chosen
Indicates that one political entity has formally incorporated another territory into its own sovereign domain.
-
E.
annexedInYear
Indicates that one entity was formally annexed or incorporated into another in the specified calendar year.
- 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_69eecda6e9dc81908452fab3ba17ed9b |
completed | April 27, 2026, 2:44 a.m. |
| NER | Named-entity recognition | batch_69f657f653448190a945b4751af8507d |
completed | May 2, 2026, 8 p.m. |
| PD | Predicate disambiguation | batch_69f6575ba12081909396036f78757a76 |
completed | May 2, 2026, 7:58 p.m. |
Created at: April 27, 2026, 3:55 a.m.