Triple
T16133557
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Farlee |
E391462
|
entity |
| Predicate | relatedName |
P3889
|
FINISHED |
| Object | Farley |
E88733
|
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: Farley | Statement: [Farlee, relatedName, Farley]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Farley Context triple: [Farlee, relatedName, Farley]
-
A.
Farley
chosen
Farley is a surname most notably associated with Jim Farley, an American business executive and CEO of Ford Motor Company.
-
B.
Farley
Farley is a rural-residential suburb in the Maitland region of New South Wales, Australia.
-
C.
Farrell
Farrell is a surname of Irish origin borne by numerous notable individuals across fields such as entertainment, sports, and politics.
-
D.
Flaherty
Flaherty is an Irish surname of Gaelic origin, derived from the Ó Flaithbheartaigh family name.
-
E.
Flaherty
Flaherty is an unincorporated community located in Meade County, Kentucky, United States.
- 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_69d87f1bb0988190b490d273dbf3fd03 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e21a02e0048190b4e2c6ff434c2d7a |
completed | April 17, 2026, 11:31 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fff7a304348190bf471f2b9279b806 |
completed | May 10, 2026, 3:12 a.m. |
Created at: April 10, 2026, 5:01 a.m.