Triple
T2939273
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | R46 subway cars |
E79343
|
entity |
| Predicate | linesServed |
P6301
|
FINISHED |
| Object | G |
E92816
|
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: G | Statement: [R46 subway cars, linesServed, G]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: G Context triple: [R46 subway cars, linesServed, G]
-
A.
Ga
Ga is a Kwa language spoken primarily by the Ga people in and around Accra, the capital region of Ghana.
-
B.
GU
GU is the two-letter ISO 3166 country code assigned to Guam, an unincorporated territory of the United States in the western Pacific Ocean.
-
C.
GG
chosen
GG was the original designation for New York City's G subway service, a crosstown line that runs through Brooklyn and Queens without entering Manhattan.
-
D.
GG
GG is the standard abbreviation for Germany’s constitution, the Basic Law for the Federal Republic of Germany.
-
E.
GR
GR is the stock ticker symbol for Goodrich Corporation, a former major American aerospace and defense company known for manufacturing aircraft systems and components.
- 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_69ad8b0fbab081908f6a61567c045d8d |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad9e0fec048190bdd70c60ec5c92cd |
completed | March 8, 2026, 4:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b08686b0388190a214ad8a615f2da5 |
completed | March 10, 2026, 9 p.m. |
Created at: March 8, 2026, 2:56 p.m.