Triple
T35705801
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | APO |
E1031713
|
entity |
| Predicate | hasParentOrganizationInFiction |
P118015
|
FINISHED |
| Object | United States intelligence community |
—
|
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: United States intelligence community | Statement: [APO, hasParentOrganizationInFiction, United States intelligence community]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasParentOrganizationInFiction Context triple: [APO, hasParentOrganizationInFiction, United States intelligence community]
-
A.
hasFictionalParentCompany
chosen
Indicates that an entity is associated with a parent company that exists only in a fictional or imaginary context.
-
B.
hasFictionalPublisher
Indicates that an entity is associated with a publisher that exists only within a fictional or imaginary context.
-
C.
setInFictionalOrganization
Indicates that an entity is located within, associated with, or takes place inside a fictional organization.
-
D.
hasChildInFiction
Indicates that a fictional work or character includes another character as their child within the fictional narrative.
-
E.
worksForFictionalOrganization
Indicates that an entity is employed by or affiliated as a worker with a fictional organization.
- 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_69f76e0d393c8190b6303c64408736db |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69ffdf47d9608190830ca23d9cef6409 |
completed | May 10, 2026, 1:28 a.m. |
| PD | Predicate disambiguation | batch_69ffdf00e2b4819082dd5cb78f316baf |
completed | May 10, 2026, 1:27 a.m. |
Created at: May 3, 2026, 4:05 p.m.