Triple
T13040051
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Front Range, Colorado |
E327167
|
entity |
| Predicate | containsCity |
P294
|
FINISHED |
| Object |
Dacono
Dacono is a small city in Weld County, Colorado, located in the northern part of the Denver metropolitan area along the Front Range.
|
E1017216
|
NE FINISHED |
How this triple was built (4 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: Dacono | Statement: [Front Range, Colorado, containsCity, Dacono]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dacono Context triple: [Front Range, Colorado, containsCity, Dacono]
-
A.
Modogashe
Modogashe is a small, remote town in northeastern Kenya known as a local trading and transit center in a semi-arid pastoral region.
-
B.
Yanaoca
Yanaoca is a small Andean town in southern Peru that serves as the administrative and commercial center of Canas Province in the Cusco Region.
-
C.
Renca
Renca is a commune and urban area in the Santiago Metropolitan Region of Chile, known for its residential neighborhoods and proximity to central Santiago.
-
D.
Durosoke
Durosoke is a popular Yoruba-language hip-hop single by Nigerian rapper Olamide, known for its catchy delivery and street-inspired lyrics.
-
E.
Dencun
Dencun is a major Ethereum network upgrade that enhances scalability and reduces transaction costs, particularly for layer-2 rollups, by introducing data-availability improvements like proto-danksharding.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Dacono Triple: [Front Range, Colorado, containsCity, Dacono]
Generated description
Dacono is a small city in Weld County, Colorado, located in the northern part of the Denver metropolitan area along the Front Range.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Dacono Target entity description: Dacono is a small city in Weld County, Colorado, located in the northern part of the Denver metropolitan area along the Front Range.
-
A.
Modogashe
Modogashe is a small, remote town in northeastern Kenya known as a local trading and transit center in a semi-arid pastoral region.
-
B.
Yanaoca
Yanaoca is a small Andean town in southern Peru that serves as the administrative and commercial center of Canas Province in the Cusco Region.
-
C.
Renca
Renca is a commune and urban area in the Santiago Metropolitan Region of Chile, known for its residential neighborhoods and proximity to central Santiago.
-
D.
Durosoke
Durosoke is a popular Yoruba-language hip-hop single by Nigerian rapper Olamide, known for its catchy delivery and street-inspired lyrics.
-
E.
Dencun
Dencun is a major Ethereum network upgrade that enhances scalability and reduces transaction costs, particularly for layer-2 rollups, by introducing data-availability improvements like proto-danksharding.
- F. None of above. chosen
Provenance (5 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_69d8076e64308190904fb5c93517c901 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d9804d8e3081909584c93df099859a |
completed | April 10, 2026, 10:57 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6cbd2f6a481909fdd418e7ad3cc22 |
completed | May 3, 2026, 4:15 a.m. |
| NEDg | Description generation | batch_69f6cd0d21e08190855dcbee000fc25d |
completed | May 3, 2026, 4:20 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f6ce6b220c8190b1f49a9b2bfce692 |
completed | May 3, 2026, 4:26 a.m. |
Created at: April 9, 2026, 8:55 p.m.