Triple
T3394968
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | North Shore (Oahu) |
E71505
|
entity |
| Predicate | distanceFromHonolulu |
P49393
|
FINISHED |
| Object | approximately 30 miles |
—
|
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 30 miles | Statement: [North Shore (Oahu), distanceFromHonolulu, approximately 30 miles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromHonolulu Context triple: [North Shore (Oahu), distanceFromHonolulu, approximately 30 miles]
-
A.
distanceFromMaui
Indicates the measured or specified distance between an entity and the location of Maui.
-
B.
distanceFromPagoPago
Indicates the spatial distance between a given entity and the location of Pago Pago.
-
C.
distanceFromKailuaKonaMiles
Indicates the physical distance, measured in miles, between an entity and Kailua-Kona.
-
D.
distanceFromMiami
Indicates the spatial distance between a given entity’s location and the city of Miami.
-
E.
distanceToLosAngeles
Indicates the measured or calculated distance between a given entity’s location and the city of Los Angeles.
- 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_69ad85a9c4a88190a854019341cb3b60 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb85487088190b8a4ec546ff8a461 |
completed | March 8, 2026, 5:56 p.m. |
| PD | Predicate disambiguation | batch_69adadf705608190975423779430cc58 |
completed | March 8, 2026, 5:12 p.m. |
| PDg | Predicate description generation | batch_69adb2e426b88190b82d9830149b142e |
completed | March 8, 2026, 5:33 p.m. |
Created at: March 8, 2026, 3:14 p.m.