Triple
T20265063
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lauren Hutchinson |
E498944
|
entity |
| Predicate | thematicFocusOfWork |
P109058
|
FINISHED |
| Object | social struggles |
—
|
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: social struggles | Statement: [Lauren Hutchinson, thematicFocusOfWork, social struggles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: thematicFocusOfWork Context triple: [Lauren Hutchinson, thematicFocusOfWork, social struggles]
-
A.
thematicArea
Indicates the subject or item is associated with, or falls under, a particular thematic area or topic of focus.
-
B.
notableWorkFocus
Indicates that a notable work primarily centers on, addresses, or is significantly concerned with a particular subject, theme, or area.
-
C.
thematicConcept
Indicates that one entity embodies, expresses, or is centrally concerned with a particular underlying theme or conceptual idea represented by the other entity.
-
D.
creativeWorkFocus
chosen
Indicates that one entity is the primary subject, theme, or focal point of another entity’s creative work.
-
E.
thematicFunction
Indicates how an entity participates in or contributes to the role structure of an event or situation (e.g., as agent, patient, instrument, etc.).
- 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_69da6275fa6c8190952924930adee150 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e674ce27688190b31d7a6c98d3ec5e |
completed | April 20, 2026, 6:47 p.m. |
| PD | Predicate disambiguation | batch_69e55b1e5e1c8190ba8a5544b1db9e1d |
completed | April 19, 2026, 10:45 p.m. |
Created at: April 11, 2026, 11:41 p.m.