Triple
T219969
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Troup County |
E4190
|
entity |
| Predicate | isNamedForOccupation |
P365
|
FINISHED |
| Object | politician George Troup |
—
|
LITERAL 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: politician George Troup | Statement: [Troup County, isNamedForOccupation, politician George Troup]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isNamedForOccupation Context triple: [Troup County, isNamedForOccupation, politician George Troup]
-
A.
namesakeOccupation
chosen
Indicates that one entity’s occupation is the same as, or derived from, the occupation associated with the other entity’s namesake.
-
B.
nameOf
Indicates that one entity is the name or designation of another entity.
-
C.
nameGivesRiseTo
Indicates that one name, term, or designation leads to, causes, or results in the emergence or establishment of another.
-
D.
hasFamousNamesakeRole
Indicates that an entity has a role or position that shares its name with a well-known or historically notable person.
-
E.
namedAfter
Indicates that one entity has been given its name in honor of, or derived from, another entity.
- F. None of above.
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_69a2573508588190b522c2476d91acfe |
completed | Feb. 28, 2026, 2:47 a.m. |
| NER | Named-entity recognition | batch_69a25efd0df48190b8fef4c422a1265f |
completed | Feb. 28, 2026, 3:20 a.m. |
| PD | Predicate disambiguation | batch_69a25b54d790819093b35bd1a6f00f92 |
completed | Feb. 28, 2026, 3:04 a.m. |
Created at: Feb. 28, 2026, 2:53 a.m.