Triple
T16167580
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Matangi |
E392345
|
entity |
| Predicate | urbanProximity |
P36605
|
FINISHED |
| Object | on the outskirts of Hamilton |
—
|
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: on the outskirts of Hamilton | Statement: [Matangi, urbanProximity, on the outskirts of Hamilton]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: urbanProximity Context triple: [Matangi, urbanProximity, on the outskirts of Hamilton]
-
A.
hasUrbanProximity
Indicates that one entity is located near or within easy access to an urban area associated with another entity.
-
B.
nearbyUrbanCenter
chosen
Indicates that one location is geographically close to an urban center, such as a city or large town.
-
C.
featuresRegionalProximity
Indicates that one entity is located near or in close geographic proximity to a particular region or another entity.
-
D.
campusProximity
Indicates that one entity is located near, adjacent to, or within a short distance of a campus associated with the other entity.
-
E.
nearbyEconomicActivity
Indicates that there is economic activity occurring in close physical proximity to the referenced entity.
- 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_69d87f1d32208190942e4e499a80c18c |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e21eb4ea9c81908806f9771ae80148 |
completed | April 17, 2026, 11:51 a.m. |
| PD | Predicate disambiguation | batch_69e1828abb608190a99d86bce1d77de2 |
completed | April 17, 2026, 12:44 a.m. |
Created at: April 10, 2026, 5:02 a.m.