Triple
T2838914
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hawthorn Leslie and Company |
E62415
|
entity |
| Predicate | typeOfVesselsBuilt |
P11978
|
FINISHED |
| Object | destroyers |
—
|
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: destroyers | Statement: [Hawthorn Leslie and Company, typeOfVesselsBuilt, destroyers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfVesselsBuilt Context triple: [Hawthorn Leslie and Company, typeOfVesselsBuilt, destroyers]
-
A.
hasVesselType
chosen
Indicates that an entity is associated with or classified by a specific type of vessel (e.g., ship, boat, or container).
-
B.
numberOfShips
Indicates the quantity of ships associated with a given entity or situation.
-
C.
shipTypeInvolved
Indicates that a particular type or class of ship is involved or participates in a specified event, situation, or relationship.
-
D.
navalStandardType
Indicates the specific naval standard or classification system under which an entity (such as a vessel, equipment, or procedure) is defined or regulated.
-
E.
shipClass
Indicates the classification or type category to which a particular ship belongs.
- 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_69ab4c3d16bc81908b3a1c98fbd287fe |
completed | March 6, 2026, 9:50 p.m. |
| NER | Named-entity recognition | batch_69abdef015bc81909f6a2ff17b22862f |
completed | March 7, 2026, 8:16 a.m. |
| PD | Predicate disambiguation | batch_69abdd0ce8b08190ba28c192988f38ce |
completed | March 7, 2026, 8:08 a.m. |
Created at: March 6, 2026, 10:01 p.m.