Triple
T28499049
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Monorail Line |
E721184
|
entity |
| Predicate | serviceNameScript |
P29837
|
FINISHED |
| Object | Latin alphabet |
—
|
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: Latin alphabet | Statement: [Monorail Line, serviceNameScript, Latin alphabet]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: serviceNameScript Context triple: [Monorail Line, serviceNameScript, Latin alphabet]
-
A.
serviceName
Indicates the specific name or identifier of a service associated with an entity or interaction.
-
B.
serviceModuleFunction
Indicates that a function is provided or performed by a specific service module within a system.
-
C.
scriptName
chosen
Indicates the name or title of a script associated with an entity, typically identifying which script is used, referenced, or executed in a given context.
-
D.
scriptUser
Indicates that an entity functions as a user or executor of a particular script.
-
E.
serviceClass
Indicates the classification or category of service associated with or provided by an entity in the relationship.
- 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_69f01a5afdac8190ac6e72d5c100bd58 |
completed | April 28, 2026, 2:24 a.m. |
| NER | Named-entity recognition | batch_69f71f8ee0688190bd025f27993452d3 |
completed | May 3, 2026, 10:12 a.m. |
| PD | Predicate disambiguation | batch_69f71cc405c08190863565609a4c8499 |
completed | May 3, 2026, 10 a.m. |
Created at: April 28, 2026, 3:05 a.m.