Triple
T9439665
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hartt shipyard |
E227609
|
entity |
| Predicate | ownedBy |
P347
|
FINISHED |
| Object | Edmund Hartt |
E227609
|
NE 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: Edmund Hartt | Statement: [Hartt shipyard, ownedBy, Edmund Hartt]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Edmund Hartt Context triple: [Hartt shipyard, ownedBy, Edmund Hartt]
-
A.
Edmund Hartt
chosen
Edmund Hartt was an American shipbuilder best known for constructing the famed early U.S. Navy frigate USS Constitution in his Boston shipyard.
-
B.
Edward Gurney
Edward Gurney was a Republican U.S. Senator from Florida in the early 1970s, known for his prominent role on the Senate committee investigating the Watergate scandal.
-
C.
Arthur Farnsworth
Arthur Farnsworth was an American assistant director and film executive best known as the second husband of actress Bette Davis.
-
D.
William Walters
William Walters was a prominent 19th-century American businessman and art collector from Baltimore, Maryland.
-
E.
William Walters
William Walters is a fictional character appearing in Daniel Defoe’s adventure novel "Captain Singleton."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69ca843884488190ad6cbe0153088234 |
completed | March 30, 2026, 2:10 p.m. |
| NER | Named-entity recognition | batch_69cd7ee36f908190826994db91b18466 |
completed | April 1, 2026, 8:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1225345488190a1fee54f6feb321d |
completed | April 4, 2026, 2:38 p.m. |
Created at: March 30, 2026, 7:50 p.m.