Triple
T30244046
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pine Creek Railroad |
E769004
|
entity |
| Predicate | hasThemeEvent |
P174303
|
FINISHED |
| Object | holiday trains |
—
|
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: holiday trains | Statement: [Pine Creek Railroad, hasThemeEvent, holiday trains]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasThemeEvent Context triple: [Pine Creek Railroad, hasThemeEvent, holiday trains]
-
A.
hasThemeType
Indicates that something is associated with or characterized by a particular thematic category or type.
-
B.
hasThemeConnection
Indicates a relationship where one entity is linked to another through a shared or related theme, topic, or conceptual focus.
-
C.
hadThemeElement
Indicates that an entity includes, involves, or is characterized by a specific thematic element as part of its overall theme.
-
D.
hasFestivalTheme
Indicates that something is associated with, characterized by, or designed around a particular festival-related theme.
-
E.
hasThemeRelationship
Indicates a relationship where one entity is thematically related to, or centered around, another entity as its main subject or topic.
- 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_69f224820c048190b1435c4cc145acf1 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f6bcc425588190afd0dceba43ed79f |
completed | May 3, 2026, 3:11 a.m. |
| PD | Predicate disambiguation | batch_69f6ba6b1e6c8190adf9d6a257e0b744 |
completed | May 3, 2026, 3 a.m. |
| PDg | Predicate description generation | batch_69f6bbf5a8288190ae170bcbe8ab65cf |
completed | May 3, 2026, 3:07 a.m. |
Created at: April 29, 2026, 7:39 p.m.