Triple
T14986349
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LW |
E373711
|
entity |
| Predicate | appliesToTransitMode |
P45471
|
FINISHED |
| Object | subway |
—
|
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: subway | Statement: [LW, appliesToTransitMode, subway]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: appliesToTransitMode Context triple: [LW, appliesToTransitMode, subway]
-
A.
appliesToTransportMode
chosen
Indicates that a rule, condition, or characteristic is specifically associated with and relevant to a particular mode of transport.
-
B.
appliesToTransitSystem
Indicates that something (such as a rule, policy, feature, or condition) is relevant or applicable to a particular transit or transportation system.
-
C.
appliesToTransitLine
Indicates that a rule, condition, or characteristic is specifically associated with and relevant to a particular transit line.
-
D.
appliesToTransitStation
Indicates that something (such as a rule, feature, condition, or attribute) is specifically relevant or applicable to a transit station.
-
E.
hasTransitAccessTo
Indicates that one place or entity is reachable from another via public or shared transportation services.
- F. None of above.
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_69d85ccc84388190aa151e5173370c8d |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded7007588819095bb1de029a6f2eb |
completed | April 15, 2026, 12:08 a.m. |
| PD | Predicate disambiguation | batch_69de9a6169b48190a679609febd2d0e3 |
completed | April 14, 2026, 7:49 p.m. |
Created at: April 10, 2026, 2:52 a.m.