Triple
T21382339
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Red Line (CTA) |
E527391
|
entity |
| Predicate | northernTerminus |
P388
|
FINISHED |
| Object | Howard station |
—
|
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: Howard station | Statement: [Red Line (CTA), northernTerminus, Howard station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Howard station Context triple: [Red Line (CTA), northernTerminus, Howard station]
-
A.
Howard station
chosen
Howard station is a major Chicago Transit Authority rail terminal on the city's North Side that serves as a key hub for the Red, Purple, and Yellow Lines.
-
B.
Snyder station
Snyder station is an underground rapid transit stop on SEPTA’s Broad Street Line serving South Philadelphia.
-
C.
Clinton station
Clinton station is a commuter rail stop in Clinton, Connecticut, served by the Shore Line East line.
-
D.
Roosevelt station
Roosevelt station is a Tren Urbano rapid transit stop in San Juan, Puerto Rico, serving the Hato Rey district.
-
E.
Roosevelt station
Roosevelt station is an elevated Manila Light Rail Transit stop in Quezon City that serves as a key northern station on LRT Line 1.
- 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_69e0b51f363c8190944000ab5523b02b |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e8b0d1fa1c8190b3374e0bb3a971fc |
completed | April 22, 2026, 11:28 a.m. |
Created at: April 16, 2026, 5:12 p.m.