Triple
T29570317
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Big Apple Coaster |
E753284
|
entity |
| Predicate | cityThemeElement |
P87338
|
FINISHED |
| Object | Statue of Liberty replica |
—
|
NE NERFINISHED |
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: Statue of Liberty replica | Statement: [Big Apple Coaster, cityThemeElement, Statue of Liberty replica]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cityThemeElement Context triple: [Big Apple Coaster, cityThemeElement, Statue of Liberty replica]
-
A.
cityFunction
Indicates the primary role, purpose, or functional classification associated with a city (e.g., administrative, commercial, industrial, cultural).
-
B.
urbanPlanningTheme
Indicates a thematic relationship in which an entity is concerned with, addresses, or is categorized under topics related to urban planning.
-
C.
cityService
Indicates that a service is provided by, operates within, or is administered by a particular city.
-
D.
cityView
Indicates that one entity offers a view of, or overlooks, a city.
-
E.
urbanDesignElement
chosen
Indicates a relationship where something functions as a designed feature or component that shapes the form, use, or experience of an urban environment.
- 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_69f0ef7fcb4881908a933110adb9bda1 |
completed | April 28, 2026, 5:33 p.m. |
| NER | Named-entity recognition | batch_69f66d46180881908ff6b2ce3a27b9c0 |
completed | May 2, 2026, 9:31 p.m. |
| PD | Predicate disambiguation | batch_69f6659d36208190b01412600a4ed57d |
completed | May 2, 2026, 8:59 p.m. |
Created at: April 28, 2026, 5:57 p.m.