Triple
T21360839
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Costilla County |
E526772
|
entity |
| Predicate | partOf |
P40
|
FINISHED |
| Object | State of Colorado |
—
|
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: State of Colorado | Statement: [Costilla County, partOf, State of Colorado]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: State of Colorado Context triple: [Costilla County, partOf, State of Colorado]
-
A.
Colorado
chosen
Colorado is a landlocked U.S. state known for its Rocky Mountain landscapes, outdoor recreation, and cities like Denver and Boulder.
-
B.
Colorado
Colorado is a Barbacoan language spoken by indigenous communities in parts of Colombia and Ecuador.
-
C.
Colorado
Colorado is a Brazilian football club nickname commonly used for Sport Club Internacional, referencing the team's traditional red colors.
-
D.
Como, Colorado
Como, Colorado is a small historic unincorporated community and former railroad town located in the high plains of central Colorado.
-
E.
Colorado House
Colorado House is a restored 19th-century adobe hotel and commercial building located within Old Town San Diego State Historic Park, now serving as a museum that interprets early San Diego history.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b51d8a308190b09113b3b3f9bc15 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e8afa6afcc8190a1f5c599c11d2135 |
completed | April 22, 2026, 11:23 a.m. |
Created at: April 16, 2026, 5:08 p.m.