Triple
T28268057
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Camat Jatinegara |
E712761
|
entity |
| Predicate | hasTitleInIndonesian |
P65893
|
FINISHED |
| Object | Camat Jatinegara |
—
|
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: Camat Jatinegara | Statement: [Camat Jatinegara, hasTitleInIndonesian, Camat Jatinegara]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTitleInIndonesian Context triple: [Camat Jatinegara, hasTitleInIndonesian, Camat Jatinegara]
-
A.
titleInMalay
Indicates that one entity is the title of another entity expressed in the Malay language.
-
B.
hasTitleInTransliteration
Indicates that an entity has a specific title represented in a transliterated form from another writing system.
-
C.
hasTitleIn
chosen
Indicates that an entity holds or is associated with a specific title within a particular context, domain, or language.
-
D.
hasTitleInRevisedRomanization
Indicates that an entity has a specific title expressed using the Revised Romanization system for Korean.
-
E.
nameInIndonesian
Indicates that an entity is referred to by a specified name in the Indonesian language.
- 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_69efb5216c6881908020dce4aea65381 |
completed | April 27, 2026, 7:12 p.m. |
| NER | Named-entity recognition | batch_69f71996e1a48190ac59a1d66d7c44e8 |
completed | May 3, 2026, 9:47 a.m. |
| PD | Predicate disambiguation | batch_69f71820c6c88190ab38b4fa626d22cc |
completed | May 3, 2026, 9:40 a.m. |
Created at: April 27, 2026, 11:16 p.m.