Triple
T7509068
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Denver RTD |
E177468
|
entity |
| Predicate | serves |
P98
|
FINISHED |
| Object | Littleton, Colorado |
E231909
|
NE 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: Littleton, Colorado | Statement: [Denver RTD, serves, Littleton, Colorado]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Littleton, Colorado Context triple: [Denver RTD, serves, Littleton, Colorado]
-
A.
Littleton, Colorado
chosen
Littleton, Colorado is a suburban city in the Denver metropolitan area known for its historic downtown, residential neighborhoods, and proximity to the South Platte River.
-
B.
Littleton
Littleton is a village in Surrey, England, known for its proximity to Shepperton and its largely residential, semi-rural character.
-
C.
Littleton
Littleton is a suburban town in Middlesex County, Massachusetts, located northwest of Boston.
-
D.
Westminster, Colorado
Westminster, Colorado is a suburban city in the Denver metropolitan area known for its residential communities, open spaces, and proximity to both Denver and Boulder.
-
E.
Englewood, Colorado
Englewood, Colorado is a suburban city in the Denver metropolitan area known for its mix of residential neighborhoods, commercial centers, and corporate offices.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69c69f276b108190af2cc790b6554544 |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f5d052888190ae8678f9134d737c |
completed | March 27, 2026, 9:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8461035b48190ba08c0f759cafe4a |
completed | March 28, 2026, 9:20 p.m. |
Created at: March 27, 2026, 3:45 p.m.