Triple
T10140962
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Battleship New Jersey Museum and Memorial |
E231580
|
entity |
| Predicate | vesselLength |
P36727
|
FINISHED |
| Object | about 887 feet (270 meters) |
—
|
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: about 887 feet (270 meters) | Statement: [Battleship New Jersey Museum and Memorial, vesselLength, about 887 feet (270 meters)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: vesselLength Context triple: [Battleship New Jersey Museum and Memorial, vesselLength, about 887 feet (270 meters)]
-
A.
shipLength
chosen
Indicates the physical length measurement of a ship.
-
B.
maximumVesselLength
Indicates the greatest allowable or observed length of a vessel in a given context or constraint.
-
C.
naveLength
Indicates the length measurement of a building’s nave, typically from the entrance to the chancel or crossing.
-
D.
maxVesselTonnage
Indicates the maximum tonnage capacity that a vessel is allowed or designed to carry.
-
E.
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.
- 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_69ca848364f881908a24366a6feec1db |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cdeb2425008190a92c5148ed703d5c |
completed | April 2, 2026, 4:05 a.m. |
| PD | Predicate disambiguation | batch_69cd4ba4f5d88190ba68e63be10b08c7 |
completed | April 1, 2026, 4:45 p.m. |
Created at: March 30, 2026, 9:07 p.m.