Triple
T8031337
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Glasgow St Enoch railway station |
E186984
|
entity |
| Predicate | hadTrainShedMaterial |
P1272
|
FINISHED |
| Object | iron and glass |
—
|
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: iron and glass | Statement: [Glasgow St Enoch railway station, hadTrainShedMaterial, iron and glass]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hadTrainShedMaterial Context triple: [Glasgow St Enoch railway station, hadTrainShedMaterial, iron and glass]
-
A.
hasStationBuildingMaterial
Indicates that a station’s building is constructed from, or primarily composed of, a specified material.
-
B.
hasReconstructionMaterial
Indicates that something is associated with, composed of, or utilizes a particular material for its reconstruction.
-
C.
materialUsed
chosen
Indicates that one entity is made from, incorporates, or utilizes the other entity as its material or substance.
-
D.
trainShedType
Indicates the specific kind or classification of shed associated with a train or railway facility.
-
E.
materialTransportedFrom
Indicates that a material or substance is moved or carried from a specified source location to another place.
- 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_69ca82ae2d1081909dbfee42b41db419 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3eef921081908d0ea21f142c175a |
completed | March 31, 2026, 3:26 a.m. |
| PD | Predicate disambiguation | batch_69cb049688208190b32088bd2c5930bc |
completed | March 30, 2026, 11:17 p.m. |
Created at: March 30, 2026, 5:22 p.m.