Triple
T29667448
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Strom Thurmond statue |
E750566
|
entity |
| Predicate | hasInscriptionTopic |
P24066
|
FINISHED |
| Object | public service of Strom Thurmond |
—
|
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: public service of Strom Thurmond | Statement: [Strom Thurmond statue, hasInscriptionTopic, public service of Strom Thurmond]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasInscriptionTopic Context triple: [Strom Thurmond statue, hasInscriptionTopic, public service of Strom Thurmond]
-
A.
hasCollaborationTopic
Indicates that two or more entities are engaged in a collaboration focused on a specified topic or subject area.
-
B.
hasCurriculumTheme
Indicates that an educational program, course, or curriculum is associated with a specific overarching theme or focus area.
-
C.
includesTopics
chosen
Indicates that one entity contains, covers, or addresses the specified topics as part of its content or scope.
-
D.
hasMosaicSubject
Indicates that something is the depicted subject or main theme represented within a mosaic.
-
E.
hasNotableSubject
Indicates that an entity is associated with a subject that is particularly significant, prominent, or noteworthy in relation to it.
- 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_69f0d62418a08190a401b127adf9f8a6 |
completed | April 28, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69fea1f5d8c481908dc3351dc9ecef7f |
completed | May 9, 2026, 2:54 a.m. |
| PD | Predicate disambiguation | batch_69fea06b6fe0819095bf4c1bc9809927 |
completed | May 9, 2026, 2:48 a.m. |
Created at: April 28, 2026, 7:02 p.m.