Triple
T4220825
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United States Attorney for the District of Colorado |
E94334
|
entity |
| Predicate | numberOfPeerDistricts |
P1679
|
FINISHED |
| Object | 93 United States Attorney districts |
—
|
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: 93 United States Attorney districts | Statement: [United States Attorney for the District of Colorado, numberOfPeerDistricts, 93 United States Attorney districts]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfPeerDistricts Context triple: [United States Attorney for the District of Colorado, numberOfPeerDistricts, 93 United States Attorney districts]
-
A.
numberOfDistricts
chosen
Indicates the total count of districts associated with a given entity or area.
-
B.
eachDistrictElects
Indicates that every electoral district selects or chooses its own representative or set of representatives.
-
C.
numberOfSenateDistricts
Indicates the total count of senate districts associated with a given entity or jurisdiction.
-
D.
hasNumberOfCouncillors
Indicates the relationship that specifies how many councillors are associated with a given entity.
-
E.
includesDistrict
Indicates that one administrative or geographic entity contains or encompasses a specific district within its boundaries.
- 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_69b3451997e08190851db4a9a588837d |
completed | March 12, 2026, 10:58 p.m. |
| NER | Named-entity recognition | batch_69b34e4bf6088190926b982039a12079 |
completed | March 12, 2026, 11:37 p.m. |
| PD | Predicate disambiguation | batch_69b347f1d7b48190bd8974c03c7dc937 |
completed | March 12, 2026, 11:10 p.m. |
Created at: March 12, 2026, 11:04 p.m.