Triple
T5952111
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Training Ship Golden Bear |
E132422
|
entity |
| Predicate | portVisits |
P60586
|
FINISHED |
| Object | Pacific ports |
—
|
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: Pacific ports | Statement: [Training Ship Golden Bear, portVisits, Pacific ports]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: portVisits Context triple: [Training Ship Golden Bear, portVisits, Pacific ports]
-
A.
portActivity
Indicates the level or type of operational activity occurring at a port, such as ship movements, cargo handling, or related maritime operations.
-
B.
visitorCount
Indicates the number of visitors associated with a particular entity, context, or time period.
-
C.
visits
chosen
Indicates that one entity goes to or spends time at the location or presence of another entity.
-
D.
scopeOfVisits
Indicates the range, extent, or boundaries within which visits or visiting activities occur or are applicable.
-
E.
visitorFrequency
Indicates how often a visitor comes to or interacts with a particular entity or location.
- 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_69c0086b05cc8190a8f36a96927a525c |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c03ee10b308190afe38b904ae7c5f7 |
completed | March 22, 2026, 7:11 p.m. |
| PD | Predicate disambiguation | batch_69c0335806788190b6488ca8b73f7a63 |
completed | March 22, 2026, 6:22 p.m. |
Created at: March 22, 2026, 4:02 p.m.