Triple
T2405133
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ffestiniog |
E50258
|
entity |
| Predicate | hasTransportHeritage |
P2411
|
FINISHED |
| Object | narrow-gauge railways |
—
|
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: narrow-gauge railways | Statement: [Ffestiniog, hasTransportHeritage, narrow-gauge railways]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTransportHeritage Context triple: [Ffestiniog, hasTransportHeritage, narrow-gauge railways]
-
A.
hasHeritage
Indicates that an entity possesses or is associated with a particular cultural, ethnic, or ancestral background.
-
B.
hasIndustrialHeritage
chosen
Indicates that an entity possesses or is associated with historically significant industrial sites, structures, or practices.
-
C.
hasHeritageFeature
Indicates that an entity possesses or includes a feature recognized as part of cultural, historical, or natural heritage.
-
D.
hasHistoricSite
Indicates that an entity possesses, contains, or is associated with a place recognized for its historical significance.
-
E.
transportationTypeHistoricallyImportant
Indicates that a mode of transportation has played a significant role or had notable impact in historical events, periods, or developments.
- 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_69a88b0339a88190a1207333cd271cc9 |
completed | March 4, 2026, 7:41 p.m. |
| NER | Named-entity recognition | batch_69abceab9ce881909ae0a2f34515c11e |
completed | March 7, 2026, 7:07 a.m. |
| PD | Predicate disambiguation | batch_69abc5a530e8819094105aa92dfaf6b3 |
completed | March 7, 2026, 6:28 a.m. |
Created at: March 4, 2026, 7:58 p.m.