Triple
T4269057
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Gallery of Madame Liu-Tsong |
E96894
|
entity |
| Predicate | leadActorEthnicity |
P55096
|
FINISHED |
| Object | Chinese American |
—
|
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: Chinese American | Statement: [The Gallery of Madame Liu-Tsong, leadActorEthnicity, Chinese American]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: leadActorEthnicity Context triple: [The Gallery of Madame Liu-Tsong, leadActorEthnicity, Chinese American]
-
A.
portrayalNationalityOfActor
Indicates that an actor portrays a character of a specified nationality in a performance or work.
-
B.
leadActorSexualOrientation
Indicates the sexual orientation of the lead actor in a work or production.
-
C.
playedBy
Indicates that a role, character, or performance is portrayed or executed by a specific person or agent.
-
D.
starredActor
Indicates that an actor performed a leading or significant role in a particular production or work.
-
E.
leadActress
Indicates that the subject is the primary female performer in the specified film, show, or production.
- F. None of above. chosen
Provenance (4 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_69b34543f06c8190915ebb1a4574ffa9 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b34ff913608190b6ccf4a85057b07b |
completed | March 12, 2026, 11:44 p.m. |
| PD | Predicate disambiguation | batch_69b347f8dcb08190a725c1f7fb5a7466 |
completed | March 12, 2026, 11:10 p.m. |
| PDg | Predicate description generation | batch_69b34e0606488190baadf469a1afc3c2 |
completed | March 12, 2026, 11:36 p.m. |
Created at: March 12, 2026, 11:07 p.m.