Triple
T25625641
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Portrait of Mrs. Siddons |
E642421
|
entity |
| Predicate | portrayedPersonNotableFor |
P41131
|
FINISHED |
| Object | tragedy acting |
—
|
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: tragedy acting | Statement: [Portrait of Mrs. Siddons, portrayedPersonNotableFor, tragedy acting]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: portrayedPersonNotableFor Context triple: [Portrait of Mrs. Siddons, portrayedPersonNotableFor, tragedy acting]
-
A.
notablePortraitSubject
Indicates that the subject is a person who is prominently or famously depicted in a portrait created by the other entity.
-
B.
notableDepictionBy
Indicates that an entity is significantly portrayed or represented by a particular creator, work, or medium.
-
C.
namedPersonNotableFor
Indicates that a person is especially known or recognized for a particular work, role, achievement, or characteristic.
-
D.
depictsNotablePerson
chosen
Indicates that one entity visually represents or portrays a person who is considered notable or significant.
-
E.
portrayerKnownFor
Indicates that a person is especially recognized or famous for portraying a particular role, character, or work.
- 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_69e77e7bd4548190a0c691b8a2f27ff1 |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f6640168948190811bd5f933a87cf5 |
completed | May 2, 2026, 8:52 p.m. |
| PD | Predicate disambiguation | batch_69f6633451948190bcc0410602bb4914 |
completed | May 2, 2026, 8:48 p.m. |
Created at: April 21, 2026, 5:14 p.m.