Triple
T2634198
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Metropolitan Railway |
E59705
|
entity |
| Predicate | usedConstructionMethod |
P625
|
FINISHED |
| Object | cut-and-cover |
—
|
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: cut-and-cover | Statement: [Metropolitan Railway, usedConstructionMethod, cut-and-cover]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedConstructionMethod Context triple: [Metropolitan Railway, usedConstructionMethod, cut-and-cover]
-
A.
constructionMethod
chosen
Indicates the technique or process by which something is built, assembled, or created.
-
B.
hasConstruction
Indicates that one entity possesses, contains, or is characterized by a particular construction, structure, or built form associated with it.
-
C.
constructionType
Indicates the specific method or style by which something is built or constructed.
-
D.
combinedConstruction
Indicates that multiple construction elements, processes, or projects are joined or executed together as a single combined construction activity.
-
E.
usedStructure
Indicates that one entity makes use of, relies on, or operates through a particular structure (physical, logical, or organizational) to perform its function or action.
- 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_69ab4ac8596c8190b34997e73d9e991c |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abd8def9bc8190b2e013abffc7b191 |
completed | March 7, 2026, 7:50 a.m. |
| PD | Predicate disambiguation | batch_69abd812849881908f956845a80e0205 |
completed | March 7, 2026, 7:47 a.m. |
Created at: March 6, 2026, 9:50 p.m.