Triple
T10624584
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Imabari Shipbuilding Saijo shipyard |
E250288
|
entity |
| Predicate | partOfIndustrySector |
P19086
|
FINISHED |
| Object | maritime industry |
—
|
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: maritime industry | Statement: [Imabari Shipbuilding Saijo shipyard, partOfIndustrySector, maritime industry]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: partOfIndustrySector Context triple: [Imabari Shipbuilding Saijo shipyard, partOfIndustrySector, maritime industry]
-
A.
isPartOfIndustry
chosen
Indicates that one entity belongs to, operates within, or is categorized under a particular industry sector.
-
B.
ownerSector
Indicates the sector or industry category to which the owner of an entity belongs.
-
C.
containsIndustry
Indicates that one entity includes or encompasses a particular industry within its scope, structure, or operations.
-
D.
hasOccupationSector
Indicates that an entity’s occupation belongs to or is categorized within a particular economic or professional sector.
-
E.
hasIndustrialSector
Indicates that an entity is associated with, operates in, or belongs to a particular industrial sector or branch of economic activity.
- 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_69d6aa5993448190a493b790b8f85010 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d6df7fe9fc81908b3b8d1dc06a829c |
completed | April 8, 2026, 11:06 p.m. |
| PD | Predicate disambiguation | batch_69d6dd7fae088190973f70c69738af49 |
completed | April 8, 2026, 10:58 p.m. |
Created at: April 8, 2026, 8:53 p.m.