Triple
T14351715
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maxine Gray |
E355867
|
entity |
| Predicate | awardReceivedInStory |
P11
|
FINISHED |
| Object | recognition for her work in child welfare |
—
|
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: recognition for her work in child welfare | Statement: [Maxine Gray, awardReceivedInStory, recognition for her work in child welfare]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: awardReceivedInStory Context triple: [Maxine Gray, awardReceivedInStory, recognition for her work in child welfare]
-
A.
awardInStoryline
Indicates that an award is given to a character or entity within the context of a specific narrative or storyline.
-
B.
awardReceived
chosen
Indicates that an entity has been granted or honored with a specific award or recognition.
-
C.
awardReceivedWith
Indicates that an entity received a specific award, optionally together with additional contextual details such as the work, role, or circumstances associated with that award.
-
D.
awardConferred
Indicates that an award or honor has been formally granted by one entity to another.
-
E.
awardCreated
Indicates that an award was established or instituted by a particular agent or 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_69d82790a7e08190877e2d349b2e8d8e |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de8f4e1e588190bdc7aaf7a2819948 |
completed | April 14, 2026, 7:02 p.m. |
| PD | Predicate disambiguation | batch_69de2a9958e881909d03ac03f135163e |
completed | April 14, 2026, 11:52 a.m. |
Created at: April 10, 2026, 1:14 a.m.