Triple
T37411164
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Geraldton–Mount Magnet Road |
E929572
|
entity |
| Predicate | hasCoastalEndpoint |
P205889
|
FINISHED |
| Object | Geraldton |
E55090
|
NE 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: Geraldton | Statement: [Geraldton–Mount Magnet Road, hasCoastalEndpoint, Geraldton]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCoastalEndpoint Context triple: [Geraldton–Mount Magnet Road, hasCoastalEndpoint, Geraldton]
-
A.
hasCoastalTerminusCountry
Indicates that one entity is a country where the coastline or coastal endpoint of another entity (such as a route, river, or infrastructure) is located.
-
B.
hasCoastalPath
Indicates that there exists a designated path or route running along or adjacent to the coastline of a given area or feature.
-
C.
hasCoastalRegion
Indicates that a place possesses at least one region that borders or is directly adjacent to a sea or ocean.
-
D.
hasCoastline
Indicates that a geographic entity is bordered by and directly touches a sea or ocean along part of its boundary.
-
E.
hasCoastalSection
Indicates that a geographic entity includes at least one section of land that directly borders a sea or ocean.
- F. None of above. chosen
Provenance (5 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_69f76ebde49481908566cd96b37ccc84 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_6a037cad051c8190b28b354b89208574 |
completed | May 12, 2026, 7:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a417107452481908ecaf3a4c1767be4 |
completed | June 28, 2026, 7:07 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.