Triple
T1414594
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lawrence Bragg |
E31884
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Lawrence |
E99879
|
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 Bragg, givenName, Lawrence]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lawrence Context triple: [Lawrence Bragg, 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
chosen
Lawrence is the formal given name of Larry Ellison, the billionaire co-founder and longtime leader of Oracle Corporation.
-
C.
Winfield
Winfield is a masculine given name most notably borne by 19th-century American military leader Winfield Scott.
-
D.
Richardson
Richardson is a suburban city in the Dallas–Fort Worth metropolitan area known for its telecommunications industry and the University of Texas at Dallas.
-
E.
Eldridge
Eldridge is an English-language surname of Old English origin, borne by various notable individuals across fields such as politics, the arts, and sports.
- 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_69a49919a994819086528951bc224775 |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c3e5f9d08190861206934cd71fd8 |
completed | March 1, 2026, 10:55 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad0e67dbf88190a2a15baca5b9e79d |
completed | March 8, 2026, 5:51 a.m. |
Created at: March 1, 2026, 7:59 p.m.