Triple
T18002462
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Biñan |
E430660
|
entity |
| Predicate | distanceFromMetroManilaApproxKm |
P57879
|
FINISHED |
| Object | 30 |
—
|
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: 30 | Statement: [Biñan, distanceFromMetroManilaApproxKm, 30]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromMetroManilaApproxKm Context triple: [Biñan, distanceFromMetroManilaApproxKm, 30]
-
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.
distanceToIloiloCityCenter_km
Indicates the physical distance, measured in kilometers, from an entity’s location to the center of Iloilo City.
-
D.
approxDistanceFromCebuCity
Indicates that one entity is located at an approximate distance from Cebu City.
-
E.
distanceFromLuzon
Indicates the measured spatial distance between a given entity or location and the region of Luzon.
- 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_69d8b904530081908bf341d842464856 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4b3e9498c8190bdfa7a53b0c0d8db |
completed | April 19, 2026, 10:52 a.m. |
| PD | Predicate disambiguation | batch_69e3f90039e4819080527f860dca042e |
completed | April 18, 2026, 9:34 p.m. |
Created at: April 10, 2026, 10:23 a.m.