Triple
T16014757
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Indooroopilly |
E388435
|
entity |
| Predicate | hasShoppingAmenity |
P16039
|
FINISHED |
| Object | cinema complex |
—
|
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: cinema complex | Statement: [Indooroopilly, hasShoppingAmenity, cinema complex]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasShoppingAmenity Context triple: [Indooroopilly, hasShoppingAmenity, cinema complex]
-
A.
hasShoppingMall
chosen
Indicates that one entity possesses, contains, or includes a shopping mall within its area or domain.
-
B.
hasCivicAmenity
Indicates that an entity possesses, provides, or is associated with a public facility or service intended for community use.
-
C.
hasAisles
Indicates that a location or structure contains one or more aisles as part of its internal layout or organization.
-
D.
hasConvenienceStore
Indicates that one entity possesses, contains, or is associated with a convenience store.
-
E.
hasGoodsFacilities
Indicates that a location or entity is equipped with facilities for handling, storing, or processing goods or cargo.
- 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_69d86dabcb7c8190b6a39d6831d2fa1b |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e1858a00888190b8505071575dc56f |
completed | April 17, 2026, 12:57 a.m. |
| PD | Predicate disambiguation | batch_69e1826a4f7c8190aba6d4f1075141b0 |
completed | April 17, 2026, 12:44 a.m. |
Created at: April 10, 2026, 4:55 a.m.