Triple
T5893599
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Western Indonesia |
E131049
|
entity |
| Predicate | closestTo |
P67182
|
FINISHED |
| Object | mainland Southeast Asia |
—
|
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: mainland Southeast Asia | Statement: [Western Indonesia, closestTo, mainland Southeast Asia]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: closestTo Context triple: [Western Indonesia, closestTo, mainland Southeast Asia]
-
A.
closerTo
Indicates that one entity is at a smaller distance to a reference entity than another entity is.
-
B.
nearbyTo
Indicates that one entity is located close in distance or position to another entity.
-
C.
nearestPass
Indicates that one entity is the closest in distance or proximity to another entity compared to all other possible entities or paths.
-
D.
nearestPointTo
Indicates the point that is closest in distance to a given reference point or object among a set of candidates.
-
E.
isCloseTo
Indicates that one entity is physically or conceptually near another, within a relatively short distance or range.
- F. None of above. chosen
Provenance (4 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_69c00857439c819095950754176aa58a |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0400f1af881908d376ea4793f6dea |
completed | March 22, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_69c0334dc8248190b7394dcece362d52 |
completed | March 22, 2026, 6:22 p.m. |
| PDg | Predicate description generation | batch_69c0400dbec08190b2ef73689b2c0c31 |
completed | March 22, 2026, 7:16 p.m. |
Created at: March 22, 2026, 3:58 p.m.