Triple
T37404205
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pomio |
E929077
|
entity |
| Predicate | distanceToKokopo |
P205886
|
FINISHED |
| Object | remote and difficult to access by land |
—
|
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: remote and difficult to access by land | Statement: [Pomio, distanceToKokopo, remote and difficult to access by land]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToKokopo Context triple: [Pomio, distanceToKokopo, remote and difficult to access by land]
-
A.
distanceFromTutukaka
Indicates the measured distance between a given entity or location and Tutukaka.
-
B.
distanceToKaikohe
Indicates the spatial distance between a given location or entity and the town of Kaikohe.
-
C.
distanceFromMasaka_km
Indicates the physical distance, measured in kilometers, between an entity and the location Masaka.
-
D.
distanceFromKaunakakaiMiles
Indicates the physical distance, measured in miles, between an entity and the location of Kaunakakai.
-
E.
distanceToKotor
Indicates the measured distance between a given entity’s location and the location of Kotor.
- 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_69f76ebbf79c8190b85bbcf3a6be57e4 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_6a037cad051c8190b28b354b89208574 |
completed | May 12, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_6a037a13a1308190a202df66f4781855 |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c842b2c819082f1d2db995ac2eb |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 3, 2026, 4:16 p.m.