Triple
T3797949
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | UChicago Argonne, LLC |
E91618
|
entity |
| Predicate | managesFacilityType |
P4904
|
FINISHED |
| Object | United States national 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: United States national laboratory | Statement: [UChicago Argonne, LLC, managesFacilityType, United States national laboratory]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: managesFacilityType Context triple: [UChicago Argonne, LLC, managesFacilityType, United States national laboratory]
-
A.
regulatesFacility
Indicates that one entity has authority to control, oversee, or set rules governing the operation or behavior of a facility.
-
B.
hasFacilityType
Indicates that an entity possesses or is associated with a specific type or category of facility.
-
C.
operatesFacility
chosen
Indicates that an entity is responsible for running, managing, or controlling the operations of a particular facility.
-
D.
userFacility
Indicates a relationship where a user is associated with, has access to, or operates within a particular facility.
-
E.
campusFacilityType
Indicates the specific kind of facility a campus location is classified as (e.g., library, laboratory, residence hall).
- 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_69aed96354f48190a768966d6bd19b04 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aee8db8a288190afd1e3b9dcf02e97 |
completed | March 9, 2026, 3:35 p.m. |
| PD | Predicate disambiguation | batch_69aee7461abc8190945716f4b93e1a18 |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:15 p.m.