Triple
T18309701
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Santa Rosa, Laguna |
E438588
|
entity |
| Predicate | distanceFromMetroManila |
P57879
|
FINISHED |
| Object | approximately 38 kilometers |
—
|
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: approximately 38 kilometers | Statement: [Santa Rosa, Laguna, distanceFromMetroManila, approximately 38 kilometers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromMetroManila Context triple: [Santa Rosa, Laguna, distanceFromMetroManila, approximately 38 kilometers]
-
A.
distanceFromManila
chosen
Indicates the measured spatial distance between a given entity’s location and the city of Manila.
-
B.
distanceFromDavaoCity
Indicates the measured spatial distance between a given location and Davao City.
-
C.
distanceFromLuzon
Indicates the measured spatial distance between a given entity or location and the region of Luzon.
-
D.
approxDistanceFromCebuCity
Indicates that one entity is located at an approximate distance from Cebu City.
-
E.
distanceToDavaoCity
Indicates the measured distance between a given entity’s location and Davao City.
- 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_69d8b915e3e881909125d760c15d0c29 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e5021709f88190a8047dd57edc2029 |
completed | April 19, 2026, 4:25 p.m. |
| PD | Predicate disambiguation | batch_69e44fdf43d08190bbcfb6b1fe3cc0ee |
completed | April 19, 2026, 3:45 a.m. |
Created at: April 10, 2026, 10:36 a.m.