Triple
T4380153
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Port of Batangas |
E99107
|
entity |
| Predicate | hasApproxDistanceTo |
P37106
|
FINISHED |
| Object | 110 kilometers south of Manila |
—
|
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: 110 kilometers south of Manila | Statement: [Port of Batangas, hasApproxDistanceTo, 110 kilometers south of Manila]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasApproxDistanceTo Context triple: [Port of Batangas, hasApproxDistanceTo, 110 kilometers south of Manila]
-
A.
approximateDistanceFrom
chosen
Indicates an estimated or rough measure of how far one entity is from another.
-
B.
isCloseTo
Indicates that one entity is physically or conceptually near another, within a relatively short distance or range.
-
C.
hasApproximateDistanceScale
Indicates that one entity is related to another by a distance measure that is approximate or estimated rather than exact.
-
D.
hasApproximateCoordinates
Indicates that an entity is associated with location coordinates that are estimated or imprecise rather than exact.
-
E.
hasApproximateDrivingDistanceFrom
Indicates that one entity is located at an estimated or approximate driving distance from another entity, typically measured along road routes rather than as a precise or exact value.
- 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_69b3454ea8f48190a49c2436624d6ef6 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3524154dc81908532cdf997dcb802 |
completed | March 12, 2026, 11:54 p.m. |
| PD | Predicate disambiguation | batch_69b34f557fe8819085032bf7f0cea5dc |
completed | March 12, 2026, 11:42 p.m. |
Created at: March 12, 2026, 11:18 p.m.