Triple
T19198643
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | M.T.A. |
E470039
|
entity |
| Predicate | title |
P38
|
FINISHED |
| Object | M.T.A. |
—
|
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: M.T.A. | Statement: [M.T.A., title, M.T.A.]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: M.T.A. Context triple: [M.T.A., title, M.T.A.]
-
A.
M.T.A.
chosen
"M.T.A." is a humorous American folk song, popularized by the Kingston Trio, about a man doomed to ride Boston’s subway system forever because he lacks the fare to get off.
-
B.
METRO
METRO is the public-facing brand name used by Metro Transit for its network of buses, trains, and other mass transportation services.
-
C.
Miles&Go
Miles&Go is TAP Air Portugal’s loyalty program that allows members to earn and redeem miles for flights, upgrades, and other travel-related benefits.
-
D.
MTA
MTA is the Hungarian Academy of Sciences, Hungary’s foremost scholarly institution overseeing and supporting scientific research across disciplines.
-
E.
MTA
MTA is the National Rail station code for Mountain Ash railway station in Wales.
- 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_69d8dd0ad9088190a173b32657ae2e7a |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5f8a8daac8190b3558a1388596fb0 |
completed | April 20, 2026, 9:58 a.m. |
Created at: April 10, 2026, 12:07 p.m.