Triple
T13417528
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pangkajene and Islands Regency |
E313250
|
entity |
| Predicate | hasMainlandArea |
P101966
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Pangkajene and Islands Regency, hasMainlandArea, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMainlandArea Context triple: [Pangkajene and Islands Regency, hasMainlandArea, yes]
-
A.
hasAdjacentMainlandArea
Indicates that one geographic area directly borders or touches a contiguous mainland region.
-
B.
hasInlandArea
chosen
Indicates that an entity possesses a portion of its territory or surface that is located away from coastal or shoreline areas.
-
C.
isMainlandTerritoryOf
Indicates that a territory constitutes the primary continental landmass belonging to a particular country or sovereign entity.
-
D.
hasMainlandLengthApproxKm
Indicates the approximate length of an entity’s mainland portion, measured in kilometers.
-
E.
hasMainlandCoastline
Indicates that a geographic entity possesses a coastline that is directly connected to a continental mainland, rather than only to islands or inland bodies of water.
- 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_69d806ad0c44819088833ae1ec9e9690 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dbaeb8416c8190a00dde0917c26f51 |
completed | April 12, 2026, 2:39 p.m. |
| PD | Predicate disambiguation | batch_69d9a0355de48190bb3fb96912e20df3 |
completed | April 11, 2026, 1:13 a.m. |
Created at: April 9, 2026, 9:39 p.m.