Triple
T10313311
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Island Garden City of Samal |
E241950
|
entity |
| Predicate | distanceToDavaoCity |
P93317
|
FINISHED |
| Object | about 2 kilometers across the Davao Gulf |
—
|
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 2 kilometers across the Davao Gulf | Statement: [Island Garden City of Samal, distanceToDavaoCity, about 2 kilometers across the Davao Gulf]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToDavaoCity Context triple: [Island Garden City of Samal, distanceToDavaoCity, about 2 kilometers across the Davao Gulf]
-
A.
distanceFromManila
Indicates the measured spatial distance between a given entity’s location and the city of Manila.
-
B.
approxDistanceFromCebuCity
Indicates that one entity is located at an approximate distance from Cebu City.
-
C.
distanceToKota
Indicates the measured distance between a given entity and the location referred to as Kota.
-
D.
distanceToDaNang_km
Indicates the distance, measured in kilometers, between a given location and Da Nang.
-
E.
approxTravelTimeFromCebuCity
Indicates the estimated amount of time it typically takes to travel from Cebu City to another location.
- 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_69d381ac38808190a8ca7457c85b625b |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d7ccb7ec8190a538cf279e48116e |
completed | April 7, 2026, 10:09 a.m. |
| PD | Predicate disambiguation | batch_69d4d1f4f354819080b4ed4bc61bdff6 |
completed | April 7, 2026, 9:44 a.m. |
| PDg | Predicate description generation | batch_69d4d7cada7881908beba55a1dc9ecb9 |
completed | April 7, 2026, 10:09 a.m. |
Created at: April 6, 2026, 11:48 a.m.