Triple
T17847438
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Naga City, Cebu |
E445700
|
entity |
| Predicate | distanceToCebuCity |
P88372
|
FINISHED |
| Object | approximately 21 km south |
—
|
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 21 km south | Statement: [Naga City, Cebu, distanceToCebuCity, approximately 21 km south]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToCebuCity Context triple: [Naga City, Cebu, distanceToCebuCity, approximately 21 km south]
-
A.
approxDistanceFromCebuCity
chosen
Indicates that one entity is located at an approximate distance from Cebu City.
-
B.
approxTravelTimeFromCebuCity
Indicates the estimated amount of time it typically takes to travel from Cebu City to another location.
-
C.
distanceFromManila
Indicates the measured spatial distance between a given entity’s location and the city of Manila.
-
D.
distanceToDavaoCity
Indicates the measured distance between a given entity’s location and Davao City.
-
E.
distanceToDumagueteCity
Indicates the spatial distance between a given location and Dumaguete 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_69d8b9f26f18819089c9e43250bee6ae |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e48ffc5fec8190adc66f7b0e264d5f |
completed | April 19, 2026, 8:19 a.m. |
| PD | Predicate disambiguation | batch_69e3d8e266888190ae976b4b7d5b886f |
completed | April 18, 2026, 7:17 p.m. |
Created at: April 10, 2026, 10:16 a.m.