Triple
T3845206
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kelvinhall subway station |
E93551
|
entity |
| Predicate | networkLengthContext |
P51884
|
FINISHED |
| Object | part of circular Glasgow Subway |
—
|
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: part of circular Glasgow Subway | Statement: [Kelvinhall subway station, networkLengthContext, part of circular Glasgow Subway]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: networkLengthContext Context triple: [Kelvinhall subway station, networkLengthContext, part of circular Glasgow Subway]
-
A.
networkLength
Indicates the total measured extent or distance covered by a network (e.g., of connections, links, or paths).
-
B.
circuitLength
Indicates the total measured length or distance of a circuit or closed path.
-
C.
networkModel
Indicates a relationship where an entity is represented or organized according to a specific network-based structure or framework.
-
D.
network
Indicates that one entity is connected to or interacts with another through a system of relationships, communication, or information exchange.
-
E.
networkType
Indicates the category or kind of network associated with or used by an entity (e.g., wired, wireless, virtual, or specific protocol-based networks).
- 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_69aed96ce578819084ab16e3439976c9 |
completed | March 9, 2026, 2:30 p.m. |
| NER | Named-entity recognition | batch_69aeebb655c081909ec5ff3d09eb4778 |
completed | March 9, 2026, 3:48 p.m. |
| PD | Predicate disambiguation | batch_69aee750377c8190af70c79768c0edd8 |
completed | March 9, 2026, 3:29 p.m. |
| PDg | Predicate description generation | batch_69aee8d9b328819080158be59e5bcc97 |
completed | March 9, 2026, 3:35 p.m. |
Created at: March 9, 2026, 3:18 p.m.