Triple
T38342789
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | King Street (Charleston) |
E1041452
|
entity |
| Predicate | lowerSectionKnownFor |
P110087
|
FINISHED |
| Object | antiques |
—
|
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: antiques | Statement: [King Street (Charleston), lowerSectionKnownFor, antiques]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lowerSectionKnownFor Context triple: [King Street (Charleston), lowerSectionKnownFor, antiques]
-
A.
segmentKnownFor
chosen
Indicates that a specific segment or portion of something is recognized or notable for a particular characteristic, feature, or association.
-
B.
underlyingKnownFor
Indicates that one entity is fundamentally or primarily recognized as the basis or main reason for another entity’s notability or fame.
-
C.
nowKnownFor
Indicates that an entity is currently recognized or notable for a particular role, attribute, achievement, or association.
-
D.
lowerSectionType
Indicates the specific type or category assigned to the lower section of an object, structure, or entity in a larger whole.
-
E.
namedForKnownFor
Indicates that one entity is named after another entity specifically because that other entity is notable or recognized for something.
- 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_69f76e2ad95481908c920c0e5c1c3e26 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69fcc7a4d7f881908b43b960911b81e9 |
completed | May 7, 2026, 5:11 p.m. |
| PD | Predicate disambiguation | batch_69fcc589720c819089c8f500fea3c86a |
completed | May 7, 2026, 5:02 p.m. |
Created at: May 3, 2026, 4:30 p.m.