Triple
T9322189
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Manila–Hong Kong |
E224294
|
entity |
| Predicate | approximateRegionDistance |
P37106
|
FINISHED |
| Object | short‑haul |
—
|
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: short‑haul | Statement: [Manila–Hong Kong, approximateRegionDistance, short‑haul]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approximateRegionDistance Context triple: [Manila–Hong Kong, approximateRegionDistance, short‑haul]
-
A.
approximateDistanceFrom
chosen
Indicates an estimated or rough measure of how far one entity is from another.
-
B.
hasApproximateDistanceScale
Indicates that one entity is related to another by a distance measure that is approximate or estimated rather than exact.
-
C.
approximateRadius
Indicates that one entity specifies or provides an estimated value for the radius of another entity.
-
D.
featuresRegionalProximity
Indicates that one entity is located near or in close geographic proximity to a particular region or another entity.
-
E.
hasApproximateCoordinates
Indicates that an entity is associated with location coordinates that are estimated or imprecise rather than exact.
- 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_69ca8426d48481909596360f7791c7dd |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd36f2bd288190bb1556a88d9e90f3 |
completed | April 1, 2026, 3:17 p.m. |
| PD | Predicate disambiguation | batch_69cc7a61e9a4819096eb014f3791ef2e |
completed | April 1, 2026, 1:52 a.m. |
Created at: March 30, 2026, 7:38 p.m.