Triple
T24406101
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Batavia Creole |
E615315
|
entity |
| Predicate | spokenInPresentDayCity |
P109887
|
FINISHED |
| Object | Jakarta |
—
|
NE NERFINISHED |
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: Jakarta | Statement: [Batavia Creole, spokenInPresentDayCity, Jakarta]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: spokenInPresentDayCity Context triple: [Batavia Creole, spokenInPresentDayCity, Jakarta]
-
A.
spokenInUrbanArea
Indicates that an utterance or speech event occurs within a city or densely populated urban environment.
-
B.
spokenInLocality
chosen
Indicates that a language, dialect, or speech form is used or spoken within a specific locality or geographic area.
-
C.
usedInCity
Indicates that something is utilized, applied, or operates within the context or boundaries of a particular city.
-
D.
mentionsCity
Indicates that one entity refers to or brings up a particular city in some form of communication or content.
-
E.
presentDayCityIs
Indicates that one entity is the current, modern-day city corresponding to or located at the place represented by the other entity.
- 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_69e2d7e780bc81908049c779e697a7f6 |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f294dfd8d88190b831b6a8f4157980 |
completed | April 29, 2026, 11:31 p.m. |
| PD | Predicate disambiguation | batch_69f287c4a2b48190b80fb7a3c0e9b018 |
completed | April 29, 2026, 10:35 p.m. |
Created at: April 18, 2026, 2:05 a.m.