Triple
T21334997
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Orange Line (CTA) |
E526018
|
entity |
| Predicate | terminus |
P388
|
FINISHED |
| Object | Loop |
—
|
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: Loop | Statement: [Orange Line (CTA), terminus, Loop]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Loop Context triple: [Orange Line (CTA), terminus, Loop]
-
A.
Loop
chosen
The Loop is Chicago’s central business district and downtown core, known for its dense cluster of skyscrapers, cultural institutions, and historic elevated train system.
-
B.
Loop
Loop is the nickname of James Merritt, likely used as a distinctive personal or professional moniker.
-
C.
Loop
Loop is a Microsoft 365 collaborative workspace app that lets teams create, share, and co-edit dynamic content blocks in real time across Microsoft’s productivity tools.
-
D.
Loop
Loop is an English alternative rock band known for its hypnotic, guitar-driven sound that helped define the late-1980s space rock and noise rock scenes.
-
E.
LOOP
LOOP is the official abbreviation for the London Loop, a long-distance walking route that circles the outskirts of Greater London.
- 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_69e0b51b90788190a4dd823d962626da |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e898d602c08190821c63e0aff42fc2 |
completed | April 22, 2026, 9:45 a.m. |
Created at: April 16, 2026, 4:43 p.m.