Triple
T10097307
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Philip Carteret |
E215901
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Carteret |
E418366
|
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: Carteret | Statement: [Philip Carteret, familyName, Carteret]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Carteret Context triple: [Philip Carteret, familyName, Carteret]
-
A.
Carteret
chosen
Carteret is a borough in Middlesex County, New Jersey, known as a residential and industrial community along the Arthur Kill waterfront.
-
B.
Beaufort
Beaufort is a small town and administrative district in the southwestern part of Sabah, Malaysia, known for its railway connection and proximity to wetlands and riverine landscapes.
-
C.
Beaufort
Beaufort is a firm, raw cow’s milk Alpine cheese from France renowned for its smooth texture and complex, nutty flavor.
-
D.
New Hanover
New Hanover is a volcanic island in the Bismarck Archipelago of Papua New Guinea, known for its rugged terrain, tropical forests, and surrounding coral reefs.
-
E.
Pettycur
Pettycur is a small coastal settlement and harbour area near Kinghorn in Fife, Scotland, known for its beach and views across the Firth of Forth.
- 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_69ca83a4947c8190823a7495dc5d96ed |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cdd07ad40081909610a7a8dc836651 |
completed | April 2, 2026, 2:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d2b6c218b08190853b0979296e2f83 |
completed | April 5, 2026, 7:23 p.m. |
Created at: March 30, 2026, 9:02 p.m.