Triple
T29874078
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | William Patterson |
E758670
|
entity |
| Predicate | shipTypeSpecialization |
P24983
|
FINISHED |
| Object | steamships |
—
|
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: steamships | Statement: [William Patterson, shipTypeSpecialization, steamships]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: shipTypeSpecialization Context triple: [William Patterson, shipTypeSpecialization, steamships]
-
A.
shipClass
Indicates the classification or type category to which a particular ship belongs.
-
B.
craftType
chosen
Indicates the specific kind or category of craft or vessel associated with an entity.
-
C.
shipTypeInvolved
Indicates that a particular type or class of ship is involved or participates in a specified event, situation, or relationship.
-
D.
shipTypeProduced
Indicates that a particular type of ship is produced, built, or manufactured by a given entity.
-
E.
shipTypeFavored
Indicates that a particular type of ship is preferred or favored over others in a given context.
- 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_69f2245d0d7081909e37ee328542bcd7 |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69f676c8ab448190900f6f8984e105a2 |
completed | May 2, 2026, 10:12 p.m. |
| PD | Predicate disambiguation | batch_69f66ac32b60819092290b2de35988d3 |
completed | May 2, 2026, 9:21 p.m. |
Created at: April 29, 2026, 5:54 p.m.