Triple
T24166895
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Granollers Centre |
E599012
|
entity |
| Predicate | hasIberianGauge |
P155566
|
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: [Granollers Centre, hasIberianGauge, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasIberianGauge Context triple: [Granollers Centre, hasIberianGauge, yes]
-
A.
hasBreakOfGaugeWith
Indicates that two connected railway lines or networks meet at a point where their track gauges differ, requiring a change of trains or transfer of cargo.
-
B.
hasMesa
Indicates that an entity possesses, contains, or is associated with a mesa (a flat-topped elevated landform).
-
C.
previouslyHadGauge
Indicates that an entity had a particular gauge or measurement instrument at some time in the past, but does not necessarily have it now.
-
D.
hasMeter
Indicates that one entity possesses, uses, or is associated with a specific meter (a measuring device or metrical pattern).
-
E.
gaugeCompatibleWith
Indicates that one gauge can be properly used with, mounted to, or function correctly in conjunction with another specified component or system.
- 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_69e288cbd62881909de32ca64a70c17b |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f27c9ddfcc819096697a844b300cce |
completed | April 29, 2026, 9:48 p.m. |
| PD | Predicate disambiguation | batch_69f1c42f942c8190b103ff29a60fef34 |
completed | April 29, 2026, 8:41 a.m. |
| PDg | Predicate description generation | batch_69f27a753ca8819095706970d368f762 |
completed | April 29, 2026, 9:39 p.m. |
Created at: April 17, 2026, 11:32 p.m.