Triple
T185929
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Robert E. Lee |
E3980
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Lee |
E762
|
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: Lee | Statement: [Robert E. Lee, familyName, Lee]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lee Context triple: [Robert E. Lee, familyName, Lee]
-
A.
Lee
chosen
Lee is a given name shared by numerous individuals across different cultures and professions.
-
B.
Neal
Neal is a masculine given name of Gaelic origin, commonly used in English-speaking countries.
-
C.
Jamie
Jamie is a given name commonly used as a diminutive or variant of James, and is borne by people of all genders in English-speaking countries.
-
D.
Jack
Jack is a common masculine given name, often used as a familiar form of John and widely featured in English-language literature and popular culture.
-
E.
Tyler
Tyler is the officer in a Masonic lodge responsible for guarding the entrance and ensuring only qualified individuals are admitted to meetings.
- 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_69a25497e2f08190a040f8c6e1842643 |
completed | Feb. 28, 2026, 2:36 a.m. |
| NER | Named-entity recognition | batch_69a2594809288190b3d3b1283e7e0d00 |
completed | Feb. 28, 2026, 2:56 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a39d0168508190b6f6766a75dd0e34 |
completed | March 1, 2026, 1:57 a.m. |
Created at: Feb. 28, 2026, 2:40 a.m.