Triple
T13149591
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pinhoe railway station |
E312427
|
entity |
| Predicate | passengerRail |
P21523
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Pinhoe railway station, passengerRail, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: passengerRail Context triple: [Pinhoe railway station, passengerRail, yes]
-
A.
hasPassengerRailConnection
Indicates that there exists a passenger rail service linking one location or transport node to another.
-
B.
trains
Indicates that one entity teaches, instructs, or coaches another entity to develop skills, knowledge, or abilities.
-
C.
isBusiestPassengerRailLineIn
Indicates that a passenger rail line is the one with the highest level of use or traffic within a specified geographic area or system.
-
D.
railServiceType
chosen
Indicates the specific category or type of rail service that applies to the relationship between the involved entities (e.g., local, express, freight).
-
E.
railroadMet
Indicates that two or more railroads encountered or connected with each other at a specific place or time.
- 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_69d806aabde48190899e13e41659cae5 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98cf054f88190b05ced98d5a22a62 |
completed | April 10, 2026, 11:51 p.m. |
| PD | Predicate disambiguation | batch_69d98bbd1d088190b7c69f37fc6eeb64 |
completed | April 10, 2026, 11:46 p.m. |
Created at: April 9, 2026, 9:11 p.m.