Triple
T9483633
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kawasan Falls |
E228706
|
entity |
| Predicate | approxTravelTimeFromCebuCity |
P88373
|
FINISHED |
| Object | about 3 hours by road |
—
|
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: about 3 hours by road | Statement: [Kawasan Falls, approxTravelTimeFromCebuCity, about 3 hours by road]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approxTravelTimeFromCebuCity Context triple: [Kawasan Falls, approxTravelTimeFromCebuCity, about 3 hours by road]
-
A.
approximateTravelTimeFromPalompon
Indicates the estimated duration it takes to travel from Palompon to another specified location.
-
B.
distanceFromManila
Indicates the measured spatial distance between a given entity’s location and the city of Manila.
-
C.
travelTimeCategory
Indicates the qualitative classification of how long a given travel or trip duration is (e.g., short, medium, long).
-
D.
approximateDrivingTimeFromLAnse
Indicates the estimated amount of time it takes to drive from L'Anse to another specified location.
-
E.
travelTimeToAirport
Indicates the amount of time required to travel from a given location to an airport.
- 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_69ca84730a5081908de282651019bf2f |
completed | March 30, 2026, 2:10 p.m. |
| NER | Named-entity recognition | batch_69cd804c859081908c261ad16b501f0d |
completed | April 1, 2026, 8:30 p.m. |
| PD | Predicate disambiguation | batch_69cca561e6b0819090aa795f3c3a2083 |
completed | April 1, 2026, 4:56 a.m. |
| PDg | Predicate description generation | batch_69cca89d0f0c8190b4528990fe708fca |
completed | April 1, 2026, 5:09 a.m. |
Created at: March 30, 2026, 7:55 p.m.