Triple
T13960504
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SMND |
E335778
|
entity |
| Predicate | codeForSystem |
P112418
|
FINISHED |
| Object | RER B station coding |
—
|
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: RER B station coding | Statement: [SMND, codeForSystem, RER B station coding]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: codeForSystem Context triple: [SMND, codeForSystem, RER B station coding]
-
A.
codeFor
Indicates that one entity serves as the implementation, encoding, or programmatic representation for another entity.
-
B.
codeForLanguage
Indicates that a piece of code is written in, or intended to be executed by, a particular programming or markup language.
-
C.
codeInNYCTInternalSystem
Indicates that something is recorded or implemented within the internal system used by NYCT (New York City Transit).
-
D.
packageSystem
Indicates a relationship where an item or component is organized, bundled, or managed within a particular packaging or distribution system.
-
E.
bodyCode
Indicates that an entity is assigned a specific body-related code used to classify or identify its physical form or condition.
- 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_69d81c61f3508190aaf2ca0dc0002c59 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2e7b2f908190aa32f22298964746 |
completed | April 14, 2026, 12:09 p.m. |
| PD | Predicate disambiguation | batch_69de05a3ccf88190b45c742db483fa08 |
completed | April 14, 2026, 9:15 a.m. |
| PDg | Predicate description generation | batch_69de239524688190a0f2408c239cfcaa |
completed | April 14, 2026, 11:23 a.m. |
Created at: April 9, 2026, 10:17 p.m.