Triple
T5843127
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mobile County |
E129640
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Semmes |
E516900
|
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: Semmes | Statement: [Mobile County, contains, Semmes]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Semmes Context triple: [Mobile County, contains, Semmes]
-
A.
Semmes
chosen
Semmes is a surname most notably associated with Raphael Semmes, a Confederate naval officer and captain of the commerce raider CSS Alabama during the American Civil War.
-
B.
Gombauld
Gombauld is a modernist painter and one of the central, satirically portrayed guests at the country-house gathering in Aldous Huxley’s novel "Crome Yellow."
-
C.
Seeman
Seeman is an Indian Tamil film director, actor, and prominent political leader who heads the Naam Tamilar Katchi party in Tamil Nadu.
-
D.
Semeka
Semeka is a former American college basketball player and coach best known for her standout career with the Tennessee Lady Volunteers under Pat Summitt.
-
E.
Sauvestre
Sauvestre is a French surname most notably associated with architect Stephen Sauvestre, who contributed to the design of the Eiffel Tower.
- 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_69c0084bd31c8190a796bb6284845e83 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c034d9da0c8190970319d0dc2fc73f |
completed | March 22, 2026, 6:28 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c0a1a2506481908a3e638c1121bfd0 |
completed | March 23, 2026, 2:12 a.m. |
Created at: March 22, 2026, 3:54 p.m.