Triple
T6435425
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | George Gordon Battle Liddy |
E129882
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Liddy |
E129881
|
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: Liddy | Statement: [George Gordon Battle Liddy, familyName, Liddy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Liddy Context triple: [George Gordon Battle Liddy, familyName, Liddy]
-
A.
Liddy
chosen
Liddy is a surname most notably associated with G. Gordon Liddy, the former FBI agent and key figure in the Watergate scandal.
-
B.
Tiffy
Tiffy is a common nickname or diminutive form of the given name Tiffany.
-
C.
Libby
Libby is a surname most notably associated with Willard F. Libby, the American chemist who developed radiocarbon dating and won the Nobel Prize in Chemistry.
-
D.
Libby
Libby is a small city in northwestern Montana known for its scenic setting near the Kootenai River and surrounding forests and mountains.
-
E.
Babo
Babo is a central character in Herman Melville’s novella "Benito Cereno," known as the cunning leader of a slave revolt who manipulates appearances aboard a Spanish slave ship.
- 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_69c0084caac48190a7bc2ad8ba44536f |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c069415c3c8190b91bd12ae79edd26 |
completed | March 22, 2026, 10:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c65fc86d0c8190a254126255a7af1b |
completed | March 27, 2026, 10:45 a.m. |
Created at: March 22, 2026, 4:45 p.m.