Triple
T24665062
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CUL |
E610650
|
entity |
| Predicate | codeForLineType |
P19896
|
FINISHED |
| Object | Metrorail main line |
—
|
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: Metrorail main line | Statement: [CUL, codeForLineType, Metrorail main line]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: codeForLineType Context triple: [CUL, codeForLineType, Metrorail main line]
-
A.
usesLineCode
chosen
Indicates that one entity employs or references a specific line code as part of its operation, identification, or communication.
-
B.
codeFor
Indicates that one entity serves as the implementation, encoding, or programmatic representation for another entity.
-
C.
servedByLineType
Indicates that a service, stop, or route is operated or covered by a specific type of transit line.
-
D.
codeForLanguage
Indicates that a piece of code is written in, or intended to be executed by, a particular programming or markup language.
-
E.
servedLineType
Indicates the type or category of service line associated with or provided in a given context.
- 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_69e2c4d505cc8190981881df06c0bf52 |
completed | April 17, 2026, 11:40 p.m. |
| NER | Named-entity recognition | batch_69f41011d8048190be70329ba0bfb7c7 |
completed | May 1, 2026, 2:29 a.m. |
| PD | Predicate disambiguation | batch_69f40ed9d47881909fcfc0d04e8d074a |
completed | May 1, 2026, 2:24 a.m. |
Created at: April 18, 2026, 2:34 a.m.