Triple
T18389921
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | River Company of the Caribbean |
E449694
|
entity |
| Predicate | hasFictionalPosition |
P61558
|
FINISHED |
| Object | telegraph operator |
—
|
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: telegraph operator | Statement: [River Company of the Caribbean, hasFictionalPosition, telegraph operator]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFictionalPosition Context triple: [River Company of the Caribbean, hasFictionalPosition, telegraph operator]
-
A.
isFictionalCharacter
Indicates that the subject is a character that exists only in fiction rather than in real life.
-
B.
hasFictionalRole
Indicates that an entity plays or is assigned a specific role within a fictional work or narrative.
-
C.
hasFictionalProperty
Indicates that an entity possesses a property, attribute, or characteristic that exists only in a fictional or imaginary context.
-
D.
hasFictionalStaffMember
chosen
Indicates that an entity includes or employs a staff member who is a fictional character.
-
E.
hasFictionalLeader
Indicates that an entity is led or governed by a leader who is a fictional character rather than a real person.
- 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_69d8b9fab8a8819086a9ddc0871715e0 |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e518416bc48190a20fa66c43d545d9 |
completed | April 19, 2026, 6 p.m. |
| PD | Predicate disambiguation | batch_69e44ff1f92c8190afbb8e85d12bf2a9 |
completed | April 19, 2026, 3:45 a.m. |
Created at: April 10, 2026, 10:46 a.m.