Triple
T33642098
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Carter G. Woodson Book Award |
E861858
|
entity |
| Predicate | alsoGives |
P161831
|
FINISHED |
| Object | honor titles |
—
|
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: honor titles | Statement: [Carter G. Woodson Book Award, alsoGives, honor titles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: alsoGives Context triple: [Carter G. Woodson Book Award, alsoGives, honor titles]
-
A.
alsoProvide
chosen
Indicates that the subject, in addition to something else already offered or specified, supplies or makes available another related item, service, or resource.
-
B.
alsoIn
Indicates that an entity participates in or belongs to an additional context, group, or location alongside another already specified one.
-
C.
alsoServes
Indicates that an entity, in addition to its primary role or function, provides service or support to another specified entity or group.
-
D.
alsoCovers
Indicates that something extends its scope or applicability to include an additional subject, area, or case beyond what was originally covered.
-
E.
alsoServedBy
Indicates that the same service, function, or role is additionally provided or fulfilled by another entity alongside the primary one.
- 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_69f3498280c48190bcc3494017d14234 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f6fb19063c81909466b329655c8583 |
completed | May 3, 2026, 7:36 a.m. |
| PD | Predicate disambiguation | batch_69f6f96badb08190994442c2aba840b1 |
completed | May 3, 2026, 7:29 a.m. |
Created at: May 1, 2026, 1:42 a.m.