Triple
T23560700
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Muppet Labs |
E579227
|
entity |
| Predicate | hasFictionalOrganizationType |
P71478
|
FINISHED |
| Object | research laboratory |
—
|
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: research laboratory | Statement: [Muppet Labs, hasFictionalOrganizationType, research laboratory]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFictionalOrganizationType Context triple: [Muppet Labs, hasFictionalOrganizationType, research laboratory]
-
A.
hasFictionalBusinessType
Indicates that an entity is associated with a type or category of fictional business it operates or represents.
-
B.
worksForFictionalOrganization
Indicates that an entity is employed by or affiliated as a worker with a fictional organization.
-
C.
hasFictionalEstablishmentType
chosen
Indicates that an establishment is associated with a particular type or category of fictional setting or institution.
-
D.
hasFictionalProductionCompany
Indicates that one entity is associated with or owns a production company that exists only within a fictional context.
-
E.
hasFictionalType
Indicates that an entity is associated with or classified under a particular type or category that is fictional rather than real.
- 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_69e245fe24588190888f3aec8407d8e3 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f1af680ee88190a23a6f9fed7ae757 |
completed | April 29, 2026, 7:12 a.m. |
| PD | Predicate disambiguation | batch_69f118afabd88190bd88f49597d120e8 |
completed | April 28, 2026, 8:29 p.m. |
Created at: April 17, 2026, 6:15 p.m.