Triple
T10624585
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Imabari Shipbuilding Saijo shipyard |
E250288
|
entity |
| Predicate | hasShipTypeSpecialization |
P11978
|
FINISHED |
| Object | ultra-large container vessels |
—
|
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: ultra-large container vessels | Statement: [Imabari Shipbuilding Saijo shipyard, hasShipTypeSpecialization, ultra-large container vessels]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasShipTypeSpecialization Context triple: [Imabari Shipbuilding Saijo shipyard, hasShipTypeSpecialization, ultra-large container vessels]
-
A.
hasShipCategory
Indicates that an entity is associated with or classified under a particular category or type of ship.
-
B.
hasShipRole
Indicates that an entity holds or is assigned a specific role or function on a ship.
-
C.
hasSpecial
Indicates that an entity possesses or is associated with a distinctive or exceptional attribute, status, or feature compared to others.
-
D.
hasVesselType
chosen
Indicates that an entity is associated with or classified by a specific type of vessel (e.g., ship, boat, or container).
-
E.
hasShippingLaneType
Indicates the specific category or type of shipping lane associated with a given route or area.
- 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.