Triple
T14202633
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Count of Luxembourg |
E352000
|
entity |
| Predicate | medievalPoliticalRole |
P100890
|
FINISHED |
| Object | imperial prince |
—
|
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: imperial prince | Statement: [Count of Luxembourg, medievalPoliticalRole, imperial prince]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: medievalPoliticalRole Context triple: [Count of Luxembourg, medievalPoliticalRole, imperial prince]
-
A.
politicalRoleMedieval
chosen
Indicates that one entity holds or is associated with a specific political office, function, or authority within a medieval sociopolitical context.
-
B.
roleInMonarchyPeriod
Indicates that an entity held a specific role or position during a defined period of a monarchy.
-
C.
aristocraticRole
Indicates that an entity holds or is associated with a formal position, title, or function within an aristocratic or noble hierarchy.
-
D.
medievalLordship
Indicates a feudal relationship in which one entity holds authority, control, or dominion over another in a medieval lord–vassal or territorial context.
-
E.
medievalState
Indicates that an entity functioned as a state or political unit during the medieval historical period.
- 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_69d827894ac0819097803e57f3227b23 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de61f589a08190b71ad4e69d92ffd0 |
completed | April 14, 2026, 3:49 p.m. |
| PD | Predicate disambiguation | batch_69de05bcd7d48190a4848d9320404aa6 |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 10, 2026, 1:05 a.m.