Triple
T31705022
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | D32 |
E809154
|
entity |
| Predicate | appliesToVessel |
P90718
|
FINISHED |
| Object | HMS Daring (D32) |
—
|
NE NERFINISHED |
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: HMS Daring (D32) | Statement: [D32, appliesToVessel, HMS Daring (D32)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: appliesToVessel Context triple: [D32, appliesToVessel, HMS Daring (D32)]
-
A.
isVesselFor
Indicates that one entity functions as a container or medium specifically used to hold, carry, or convey another entity.
-
B.
usesVesselType
Indicates that an entity performs an activity or operation by employing a specific type or category of vessel.
-
C.
hasVessel
Indicates that one entity possesses, uses, or is associated with a particular vessel (such as a container, ship, or transport medium) in the context of the described relationship or action.
-
D.
appliesToShips
chosen
Indicates that the specified condition, rule, or attribute is relevant to or affects ships.
-
E.
hasVesselType
Indicates that an entity is associated with or classified by a specific type of vessel (e.g., ship, boat, or container).
- 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_69f348de914081909fc8edff56f34dbe |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69fe72dca2f08190beff17de3d2aada6 |
completed | May 8, 2026, 11:33 p.m. |
| PD | Predicate disambiguation | batch_69fe70bca8d08190b810e1e616ceac44 |
completed | May 8, 2026, 11:24 p.m. |
Created at: April 30, 2026, 11:13 p.m.