Triple
T479483
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Suitland Federal Center |
E9134
|
entity |
| Predicate | hasTenantType |
P3277
|
FINISHED |
| Object | civilian federal agencies |
—
|
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: civilian federal agencies | Statement: [Suitland Federal Center, hasTenantType, civilian federal agencies]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTenantType Context triple: [Suitland Federal Center, hasTenantType, civilian federal agencies]
-
A.
hasTenantSince
Indicates that an entity has been the tenant of another entity starting from a specified point in time.
-
B.
hasTenants
chosen
Indicates that an entity occupies or rents space from another entity as its tenant.
-
C.
hasMemberType
Indicates that an entity includes or is associated with members belonging to a specified type or category.
-
D.
hasRateType
Indicates the specific category or scheme under which a rate (such as a price, fee, or interest) is defined or applied.
-
E.
hasAreaType
Indicates that an entity is associated with a specific kind or classification of area (e.g., urban, rural, coastal).
- 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_69a2e7ff81708190b0507a24a997232c |
completed | Feb. 28, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69a2f057c4ac819080cf43ffaa56c350 |
completed | Feb. 28, 2026, 1:40 p.m. |
| PD | Predicate disambiguation | batch_69a2edf1d5848190a7da27e2fddc136f |
completed | Feb. 28, 2026, 1:30 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.