Triple
T10185658
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lausiac History |
E236901
|
entity |
| Predicate | LaususRole |
P92589
|
FINISHED |
| Object | chamberlain of Emperor Theodosius II |
—
|
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: chamberlain of Emperor Theodosius II | Statement: [Lausiac History, LaususRole, chamberlain of Emperor Theodosius II]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: LaususRole Context triple: [Lausiac History, LaususRole, chamberlain of Emperor Theodosius II]
-
A.
legislativeRole
Indicates that an entity holds or performs a specific official position, function, or duty within a legislative body or lawmaking process.
-
B.
ethnicRole
Indicates a role, function, or social position that is specifically associated with or defined by an entity’s ethnicity.
-
C.
roleAtD.C.United
Indicates that an entity holds or held a specific role or position within the D.C. United soccer organization.
-
D.
LakatoroRole
Indicates that an entity holds or is assigned a specific role or function within the context of Lakatoro.
-
E.
sonRole
Indicates that one entity holds the role or relationship of a son with respect to another entity.
- 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_69ca84d7260c8190bfbec36762943f37 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cded36e9808190b385c5aec4889e00 |
completed | April 2, 2026, 4:14 a.m. |
| PD | Predicate disambiguation | batch_69cd7c79f21c8190a7f31b2eab80b8ba |
completed | April 1, 2026, 8:13 p.m. |
| PDg | Predicate description generation | batch_69cd7edc6cf081909d95859d880a4059 |
completed | April 1, 2026, 8:23 p.m. |
Created at: March 30, 2026, 9:12 p.m.