Triple
T6315482
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Western Province |
E141604
|
entity |
| Predicate | containsCity |
P294
|
FINISHED |
| Object | Negombo |
E78071
|
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: Negombo | Statement: [Western Province, containsCity, Negombo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Negombo Context triple: [Western Province, containsCity, Negombo]
-
A.
Negombo
chosen
Negombo is a coastal city in western Sri Lanka known historically as a strategic colonial port and today for its fishing industry and beach tourism.
-
B.
Kumba
Kumba is a renowned steel roller coaster at Busch Gardens Tampa Bay, famous for its intense inversions and smooth, high-speed layout.
-
C.
Kumba
Kumba is a major town in southwestern Cameroon known as a commercial hub and cultural crossroads where languages like Cameroonian Pidgin English are widely used.
-
D.
Chambeali
Chambeali is an Indo-Aryan language spoken primarily in the Chamba region of Himachal Pradesh in northern India.
-
E.
Mambasa
Mambasa is a town and administrative center located in the forested Ituri region of northeastern Democratic Republic of the Congo.
- 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_69c008d13b8c8190be47d896eb735605 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c064a197488190946c4637b3c829a5 |
completed | March 22, 2026, 9:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c5e478987c819085df63dab784af2a |
completed | March 27, 2026, 1:59 a.m. |
Created at: March 22, 2026, 4:28 p.m.