Triple
T2975406
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MTA New York City Subway fare system |
E80381
|
entity |
| Predicate | historicalMedium |
P44343
|
FINISHED |
| Object | token |
—
|
LITERAL 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: token | Statement: [MTA New York City Subway fare system, historicalMedium, token]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: historicalMedium Context triple: [MTA New York City Subway fare system, historicalMedium, token]
-
A.
writingMediumHistorical
Indicates that an entity historically used a particular medium or material as the means or surface for writing.
-
B.
historicalPaper
Indicates that a paper has significant historical importance or impact within its field or context.
-
C.
historicalScript
Indicates that an entity is or was written in, or otherwise associated with, a particular historical writing system or script.
-
D.
historicalCategory
Indicates that an entity is classified within a particular historical grouping, period, or type based on its time-related characteristics or context.
-
E.
historical
Indicates that the subject has existed, occurred, or been relevant in the past rather than in the present or future.
- F. None of above. chosen
Provenance (4 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_69ad8b14ffe881908ffed62f9595c867 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad998ad5308190a012ec4940eb46cb |
completed | March 8, 2026, 3:45 p.m. |
| PD | Predicate disambiguation | batch_69ad96105a708190a9ec4838cbcb1207 |
completed | March 8, 2026, 3:30 p.m. |
| PDg | Predicate description generation | batch_69ad97f5d28c8190899d90204dc43428 |
completed | March 8, 2026, 3:38 p.m. |
Created at: March 8, 2026, 2:58 p.m.