Triple
T21748387
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bedford St Johns railway station |
E536845
|
entity |
| Predicate | hasPA |
P13854
|
FINISHED |
| Object | public address system |
—
|
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: public address system | Statement: [Bedford St Johns railway station, hasPA, public address system]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPA Context triple: [Bedford St Johns railway station, hasPA, public address system]
-
A.
hasPar
Indicates a relationship where one entity has another entity as its parent.
-
B.
hasPP
Indicates that an entity is associated with a particular prepositional phrase (PP) that modifies or relates to it in a syntactic or semantic structure.
-
C.
hasPATA
Indicates that one entity possesses or is equipped with a Parallel ATA (PATA) interface or connection to another entity.
-
D.
has
chosen
Indicates that one entity possesses, owns, contains, or includes another entity as part of its state or composition.
-
E.
hasMP
Indicates that an entity is represented by, or associated with, a specific Member of Parliament (MP).
- 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_69e0c46eab808190b848242d63a17c47 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69f01a77e19c81909bf26f96aa41a7ce |
completed | April 28, 2026, 2:24 a.m. |
| PD | Predicate disambiguation | batch_69e6969c16fc8190b5126c169317d85d |
completed | April 20, 2026, 9:11 p.m. |
Created at: April 16, 2026, 6:50 p.m.