Triple
T5795131
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Civic District |
E128490
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Central Area |
E285586
|
NE 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: Central Area | Statement: [Civic District, locatedIn, Central Area]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Central Area Context triple: [Civic District, locatedIn, Central Area]
-
A.
Central Area
chosen
Central Area is the main commercial and downtown core of Singapore, encompassing its primary business, financial, and civic districts.
-
B.
Central Districts
Central Districts is a New Zealand domestic first-class cricket team representing several central regions of the country in national competitions.
-
C.
Mid-Cities region
The Mid-Cities region is a suburban area in North Texas situated between Dallas and Fort Worth, encompassing several cities that serve as residential and commercial hubs for the larger metroplex.
-
D.
Mid-City
Mid-City is a central Los Angeles neighborhood known for its diverse residential communities and proximity to major city thoroughfares and cultural districts.
-
E.
Centre
Centre was the former name of the administrative region in central France now known as Centre-Val de Loire.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69c00845ca68819081a2ce3ecca577f7 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c02a91c7788190936671bf816d3772 |
completed | March 22, 2026, 5:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c098286c1c8190b77cbaeda327dba4 |
completed | March 23, 2026, 1:32 a.m. |
Created at: March 22, 2026, 3:51 p.m.