Triple
T13611820
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lawrence Grant White |
E325207
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Lawrence |
E180561
|
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: Lawrence | Statement: [Lawrence Grant White, givenName, Lawrence]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lawrence Context triple: [Lawrence Grant White, givenName, Lawrence]
-
A.
Lawrence
Lawrence is a historic mill city in northeastern Massachusetts that developed as a major textile manufacturing center along the Merrimack River.
-
B.
Lawrence
Lawrence is a city located within Marion County in the U.S. state of Indiana.
-
C.
Lawrence
chosen
Lawrence is a masculine given name of English origin, derived from the Latin "Laurentius" meaning "from Laurentum" or "crowned with laurel."
-
D.
Lawrence
Lawrence is a college town in northeastern Kansas best known as the home of the University of Kansas and its athletic programs.
-
E.
Lawrence
Lawrence is a small rural village in the Clarence Valley region of New South Wales, Australia, known for its historic charm and riverside setting on the Clarence River.
- 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_69d8076aae28819092cf636190ee5529 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbb0aa9a1481908c6f92495aff86c6 |
completed | April 12, 2026, 2:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f77f9a9f9c81909b0a8f4f51c461ae |
completed | May 3, 2026, 5:02 p.m. |
Created at: April 9, 2026, 9:50 p.m.