Triple
T24288680
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eastern Union Railway |
E605748
|
entity |
| Predicate | developedInfrastructureType |
P110176
|
FINISHED |
| Object | railway lines |
—
|
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: railway lines | Statement: [Eastern Union Railway, developedInfrastructureType, railway lines]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: developedInfrastructureType Context triple: [Eastern Union Railway, developedInfrastructureType, railway lines]
-
A.
developedSector
Indicates that an entity has contributed to the growth, advancement, or establishment of a particular sector or industry.
-
B.
infrastructureLevel
Indicates the degree or quality of infrastructure present or provided in relation to an entity or location.
-
C.
builtInfrastructureType
chosen
Indicates the specific kind or category of built infrastructure associated with or characterized by the subject.
-
D.
hasCommercialInfrastructure
Indicates that an entity possesses or is equipped with facilities, systems, or structures that support commercial or business activities.
-
E.
urbanDevelopmentType
Indicates the specific category or nature of urban development associated with or applied to an entity (e.g., residential, commercial, mixed-use).
- 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_69e295480d0c8190846fc3c2e2da1d4c |
completed | April 17, 2026, 8:17 p.m. |
| NER | Named-entity recognition | batch_69f28f5908e08190a9f150df924a7160 |
completed | April 29, 2026, 11:08 p.m. |
| PD | Predicate disambiguation | batch_69f1c457a2908190993824395b3c365d |
completed | April 29, 2026, 8:41 a.m. |
Created at: April 18, 2026, 12:08 a.m.