Triple
T17355659
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | First Lady of Czechoslovakia |
E421928
|
entity |
| Predicate | typicalBearerRole |
P75765
|
FINISHED |
| Object | wife of the President of Czechoslovakia |
—
|
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: wife of the President of Czechoslovakia | Statement: [First Lady of Czechoslovakia, typicalBearerRole, wife of the President of Czechoslovakia]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalBearerRole Context triple: [First Lady of Czechoslovakia, typicalBearerRole, wife of the President of Czechoslovakia]
-
A.
typicalBearers
Indicates that certain entities are the usual or characteristic holders, users, or possessors of a given property, role, or attribute.
-
B.
associatedWithRoleOfNameBearer
chosen
Indicates that an entity is connected to or involved with the specific role or function held by a designated name bearer.
-
C.
typicalNameBearers
Indicates that the subject is a common or characteristic name borne by the entities in the object set.
-
D.
typicalBearersNationality
Indicates the nationality that entities of a given type or class are most commonly associated with.
-
E.
notableBearerDescription
Indicates that the subject has a notable bearer, with the object providing a textual description of that bearer’s significance or identity.
- 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_69d889d520008190a26917a95bf1c2ea |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e43a487bd8819081c6d1e4aa466d6f |
completed | April 19, 2026, 2:13 a.m. |
| PD | Predicate disambiguation | batch_69e3b02662d08190a07d0fb5c04b6f33 |
completed | April 18, 2026, 4:24 p.m. |
Created at: April 10, 2026, 5:44 a.m.