Triple
T14741978
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eureka Mountain Mine Ride |
E346369
|
entity |
| Predicate | hadQueueTheme |
P88383
|
FINISHED |
| Object | mining town |
—
|
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: mining town | Statement: [Eureka Mountain Mine Ride, hadQueueTheme, mining town]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hadQueueTheme Context triple: [Eureka Mountain Mine Ride, hadQueueTheme, mining town]
-
A.
queueAreaTheme
chosen
Indicates the thematic style or concept applied to the area where people wait in line for an attraction or service.
-
B.
hasTympanumTheme
Indicates that a subject features a specific thematic or narrative motif depicted in its tympanum (the semi-circular or triangular decorative space above a doorway or entrance).
-
C.
hasThemeType
Indicates that something is associated with or characterized by a particular thematic category or type.
-
D.
hasThemeSong
Indicates that an entity is associated with or characterized by a particular theme song.
-
E.
hasFloodTheme
Indicates that something incorporates, depicts, or centers around the theme of a flood or flooding.
- 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_69d822e6f1c88190bc494d491a907114 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69dec7367a1c819081082cc355e385fa |
completed | April 14, 2026, 11:01 p.m. |
| PD | Predicate disambiguation | batch_69de8bf9331481909582045cd567d91f |
completed | April 14, 2026, 6:48 p.m. |
Created at: April 10, 2026, 1:30 a.m.