Triple
T12963508
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aba Main Market |
E321205
|
entity |
| Predicate | hasLanguageOfCommerce |
P74986
|
FINISHED |
| Object | English |
—
|
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: English | Statement: [Aba Main Market, hasLanguageOfCommerce, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLanguageOfCommerce Context triple: [Aba Main Market, hasLanguageOfCommerce, English]
-
A.
hasLanguageOfOrders
Indicates that one entity uses or is associated with a particular language for issuing orders or commands to another entity.
-
B.
languageOfCommunications
Indicates that a specified language is used as the medium for communications associated with an entity or interaction.
-
C.
languageUsedInTrade
chosen
Indicates that a particular language is employed as a medium of communication in trade or commercial transactions between parties.
-
D.
hasLanguages
Indicates that an entity is associated with one or more languages it uses, supports, or is expressed in.
-
E.
hasLanguageOfSide
Indicates that an entity uses or is associated with a particular language on a specific side or aspect (e.g., one side of a bilingual object or interface).
- 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_69d80763bd6c819094437da5b20b01d2 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d97e59a4c88190907d05b8d57dae89 |
completed | April 10, 2026, 10:48 p.m. |
| PD | Predicate disambiguation | batch_69d97dba57988190b786ffed55687a72 |
completed | April 10, 2026, 10:46 p.m. |
Created at: April 9, 2026, 8:25 p.m.