Triple
T34711547
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | San Narciso |
E1000658
|
entity |
| Predicate | containsFictionalCompany |
P158093
|
FINISHED |
| Object | Yoyodyne, Inc. |
—
|
NE NERFINISHED |
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: Yoyodyne, Inc. | Statement: [San Narciso, containsFictionalCompany, Yoyodyne, Inc.]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: containsFictionalCompany Context triple: [San Narciso, containsFictionalCompany, Yoyodyne, Inc.]
-
A.
hasFictionalCorporation
chosen
Indicates that an entity is associated with or includes a fictional corporation within its content, setting, or narrative.
-
B.
hasFictionalCompanyMethod
Indicates that an entity employs or is associated with a particular method, approach, or technique used by a fictional company.
-
C.
hasFictionalProductionCompany
Indicates that one entity is associated with or owns a production company that exists only within a fictional context.
-
D.
fictionalCorporation
Indicates that an entity is a corporation that exists only in fiction rather than in the real world.
-
E.
hasFictionalParentCompany
Indicates that an entity is associated with a parent company that exists only in a fictional or imaginary context.
- 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_69f76dad3f108190a280fd0a2f4ee89a |
completed | May 3, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_6a008098e5dc8190b7ccad8bab780343 |
completed | May 10, 2026, 12:56 p.m. |
| PD | Predicate disambiguation | batch_6a008037267c8190990225a6ff0b3694 |
completed | May 10, 2026, 12:55 p.m. |
Created at: May 3, 2026, 3:59 p.m.