Triple
T365652
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pago Pago |
E7953
|
entity |
| Predicate | hasPortFacility |
P2836
|
FINISHED |
| Object | commercial harbor |
—
|
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: commercial harbor | Statement: [Pago Pago, hasPortFacility, commercial harbor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPortFacility Context triple: [Pago Pago, hasPortFacility, commercial harbor]
-
A.
hasPortico
Indicates that one entity (typically a building or structure) features a portico as part of its architectural design.
-
B.
hasMajorPort
Indicates that a location possesses a primary, significant seaport used for major commercial or transportation activities.
-
C.
hasPortCity
Indicates that a place or region possesses or is associated with a city that functions as its port.
-
D.
hasFacilityType
chosen
Indicates that an entity possesses or is associated with a specific type or category of facility.
-
E.
hasDiscoveryFacility
Indicates that an entity has, is associated with, or is served by a facility where discoveries (such as scientific, medical, or technological findings) are made or were made.
- 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_69a2e7e880008190a6ad7e06e5d03007 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ebe7d4d0819083daeb7686ae1914 |
completed | Feb. 28, 2026, 1:21 p.m. |
| PD | Predicate disambiguation | batch_69a2e95dbb208190b277fc5352a4ee84 |
completed | Feb. 28, 2026, 1:10 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.