Triple
T4167307
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | World Expo 88 |
E84475
|
entity |
| Predicate | impactOnCity |
P10973
|
FINISHED |
| Object | accelerated urban renewal in Brisbane |
—
|
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: accelerated urban renewal in Brisbane | Statement: [World Expo 88, impactOnCity, accelerated urban renewal in Brisbane]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: impactOnCity Context triple: [World Expo 88, impactOnCity, accelerated urban renewal in Brisbane]
-
A.
affectedCity
chosen
Indicates that a particular city is impacted or influenced by a specified event, action, or condition.
-
B.
cityOfInfluence
Indicates the city that significantly shapes, impacts, or exerts influence over a given entity.
-
C.
impactBuilding
Indicates that one entity physically collides with or strikes a building, causing an impact event.
-
D.
socialImpact
Indicates the extent to which an action, entity, or relationship affects society or communities, whether positively or negatively.
-
E.
impactCategory
Indicates the type or domain of effect that one entity or action has on another, classifying the nature of its impact.
- 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_69aed932cab48190b80ffe35f7029ae1 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af02c43a7481909eed7cb8c14deb0c |
completed | March 9, 2026, 5:26 p.m. |
| PD | Predicate disambiguation | batch_69af018fb0948190a9701b2e8e5d9bac |
completed | March 9, 2026, 5:21 p.m. |
Created at: March 9, 2026, 3:44 p.m.