Triple
T628238
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Uvalde Cemetery |
E15866
|
entity |
| Predicate | topicalConcept |
P531
|
FINISHED |
| Object | cemeteries in 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 Texas | Statement: [Uvalde Cemetery, topicalConcept, cemeteries in Texas]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: topicalConcept Context triple: [Uvalde Cemetery, topicalConcept, cemeteries in Texas]
-
A.
hasConcept
chosen
Indicates that an entity includes, embodies, or is associated with a particular concept.
-
B.
primaryTopicOf
Indicates that a given subject is the main or central topic described by another resource (such as a document, page, or record).
-
C.
philosophicalConcept
Indicates that one entity is a philosophical concept that characterizes, explains, or is thematically central to the other entity.
-
D.
introducedConcept
Indicates that one entity is responsible for presenting, defining, or bringing a new concept into use or awareness for another entity or context.
-
E.
architecturalConcept
Indicates that one entity represents or embodies an architectural concept in relation to 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_69a4935c131c8190a5378c6bf101e8cc |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a49e59e2688190b3c18b17c5db1e2b |
completed | March 1, 2026, 8:15 p.m. |
| PD | Predicate disambiguation | batch_69a49d01b29081908be87e4cd7726ff1 |
completed | March 1, 2026, 8:09 p.m. |
Created at: March 1, 2026, 7:35 p.m.