Triple
T10226957
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Confederate Cemetery, Dallas |
E243229
|
entity |
| Predicate | topicalCategory |
P87
|
FINISHED |
| Object | Cemeteries in Dallas, Texas |
—
|
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: Cemeteries in Dallas, Texas | Statement: [Confederate Cemetery, Dallas, topicalCategory, Cemeteries in Dallas, Texas]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: topicalCategory Context triple: [Confederate Cemetery, Dallas, topicalCategory, Cemeteries in Dallas, Texas]
-
A.
coreCategory
Indicates that one entity is the primary or fundamental category to which another entity belongs or is classified under.
-
B.
cosmeticCategory
Indicates that one entity is classified as belonging to a particular cosmetic or beauty product category defined by the other entity.
-
C.
categoryFocus
Indicates that one entity is the primary subject, theme, or focal point within the broader category defined by the other entity.
-
D.
textCategory
Indicates that a piece of text belongs to or is classified under a particular category or type.
-
E.
category
chosen
Indicates that one entity is classified as a member or type within the grouping or class defined by 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_69d381b0f97c819085c9b45799a5fb7c |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d23b620c8190b8a72d0eb0d16b93 |
completed | April 7, 2026, 9:45 a.m. |
| PD | Predicate disambiguation | batch_69d4d1e9798c8190b437d53d48554ba1 |
completed | April 7, 2026, 9:44 a.m. |
Created at: April 6, 2026, 11:17 a.m.