Triple
T13434051
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lejweleputswa District Municipality |
E320183
|
entity |
| Predicate | hasMajorTown |
P316
|
FINISHED |
| Object | Welkom |
E190332
|
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: Welkom | Statement: [Lejweleputswa District Municipality, hasMajorTown, Welkom]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Welkom Context triple: [Lejweleputswa District Municipality, hasMajorTown, Welkom]
-
A.
Welkom
chosen
Welkom is a South African city in the Free State province known historically for its gold mining industry and planned urban layout.
-
B.
Willkommen
"Willkommen" is the iconic opening number from the musical *Cabaret*, introducing the seedy, seductive world of the Kit Kat Klub and its enigmatic Emcee.
-
C.
Welcome
Welcome is a 2009 French drama film directed by Philippe Lioret, known for its poignant portrayal of an Iraqi Kurdish refugee in Calais who trains to swim the English Channel.
-
D.
Welcome
"Welcome" is a song best known for being part of the Back to Basics Tour setlist.
-
E.
Welcome
Welcome is an unincorporated rural community located in Coweta County, Georgia, United States.
- 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_69d80761e6cc8190a90c844589998ecc |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbaee29fec81908b07b4fca2922242 |
completed | April 12, 2026, 2:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7547880d48190af9b30e4e521a952 |
completed | May 3, 2026, 1:58 p.m. |
Created at: April 9, 2026, 9:40 p.m.