Triple
T23876551
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jakarta LRT |
E592880
|
entity |
| Predicate | servedAreaCharacteristic |
P3938
|
FINISHED |
| Object | high-traffic corridors |
—
|
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: high-traffic corridors | Statement: [Jakarta LRT, servedAreaCharacteristic, high-traffic corridors]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: servedAreaCharacteristic Context triple: [Jakarta LRT, servedAreaCharacteristic, high-traffic corridors]
-
A.
serviceAreaCharacteristic
chosen
Indicates a relationship where a service area is associated with a specific attribute or feature that characterizes it.
-
B.
areaServedType
Indicates the type or category of area that is served by an entity or service.
-
C.
areaServed
Indicates the geographic region or jurisdiction within which a service, organization, or activity is provided or applicable.
-
D.
strategicAreaServed
Indicates that an entity provides services or exerts influence within a particular area considered strategically important.
-
E.
coreAreaCharacteristic
Indicates that a characteristic or feature is specifically associated with the core area of something, rather than its peripheral or secondary parts.
- 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_69e25d23a5c88190ae3999c70ca15e08 |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1cc02277c8190b0c15d6525f3b38d |
completed | April 29, 2026, 9:14 a.m. |
| PD | Predicate disambiguation | batch_69f1614a65a88190bde1efb368a151e4 |
completed | April 29, 2026, 1:39 a.m. |
Created at: April 17, 2026, 8:15 p.m.