Triple
T28042893
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grand Bahama Shipyard |
E708594
|
entity |
| Predicate | nearbyStateMarket |
P182832
|
FINISHED |
| Object | Florida |
—
|
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: Florida | Statement: [Grand Bahama Shipyard, nearbyStateMarket, Florida]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nearbyStateMarket Context triple: [Grand Bahama Shipyard, nearbyStateMarket, Florida]
-
A.
nearbyCountryMarket
Indicates that a market is located in a country that is geographically close to another specified country.
-
B.
nearbyState
Indicates that one state is geographically adjacent to or in close proximity to another state.
-
C.
stateMarket
Indicates that a market or economic condition is associated with, regulated by, or characteristic of a particular state or governmental jurisdiction.
-
D.
nearByCityState
Indicates that a city is geographically close to or within the same general area as a specified state.
-
E.
nearbyUSBase
Indicates that one entity is geographically close to a United States military base.
- F. None of above. chosen
Provenance (4 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_69ef9b6cf538819094a633ffa67afec1 |
completed | April 27, 2026, 5:22 p.m. |
| NER | Named-entity recognition | batch_69f794f24e588190965e39b77534d53f |
completed | May 3, 2026, 6:33 p.m. |
| PD | Predicate disambiguation | batch_69f791033d288190b118029fe412b9c9 |
completed | May 3, 2026, 6:16 p.m. |
| PDg | Predicate description generation | batch_69f791cad5e08190a8a04ca283dbecaa |
completed | May 3, 2026, 6:19 p.m. |
Created at: April 27, 2026, 8:26 p.m.