Triple
T23063996
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Franklin C. Sibert |
E574980
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Franklin |
E58775
|
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: Franklin | Statement: [Franklin C. Sibert, givenName, Franklin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Franklin Context triple: [Franklin C. Sibert, givenName, Franklin]
-
A.
Franklin
Franklin McCain was an American civil rights activist best known as one of the Greensboro Four who led the 1960 Woolworth’s lunch counter sit-in in North Carolina.
-
B.
Franklin
Franklin is a town in Norfolk County, Massachusetts, serving as a terminus for the MBTA Commuter Rail system.
-
C.
Franklin
Franklin is a territorial authority district in the Auckland and Waikato regions of New Zealand, known for its mix of rural landscapes, horticulture, and small towns.
-
D.
Franklin
chosen
Franklin is a common English surname borne by numerous notable individuals across fields such as politics, science, and the arts.
-
E.
Franklin
Franklin is a wealthy, hospitable landowner and one of the storytellers in Geoffrey Chaucer’s The Canterbury Tales, known for his focus on gentility and marital harmony.
- 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_69e245bd6e4c8190bb8942245b68cad5 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f189a1f49c81909db7e0473ec2bb1b |
completed | April 29, 2026, 4:31 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0c0aeae0d08190b2f75cd2b44a0403 |
completed | May 19, 2026, 7:02 a.m. |
Created at: April 17, 2026, 3:55 p.m.