Triple
T17498091
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Madame Liu-Tsong |
E426118
|
entity |
| Predicate | starIsPioneeringFigure |
P127680
|
FINISHED |
| Object | Anna May Wong as early Asian American film and television star |
—
|
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: Anna May Wong as early Asian American film and television star | Statement: [Madame Liu-Tsong, starIsPioneeringFigure, Anna May Wong as early Asian American film and television star]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: starIsPioneeringFigure Context triple: [Madame Liu-Tsong, starIsPioneeringFigure, Anna May Wong as early Asian American film and television star]
-
A.
starIs
Indicates that one entity is identified or classified as a star in relation to another entity or context.
-
B.
starImage
Indicates that one entity is an image or visual representation of a star or stellar object.
-
C.
starKnownAs
Indicates that a particular star is referred to or identified by a specific name or designation.
-
D.
starType
Indicates the classification relationship specifying what type or category of star an astronomical object is.
-
E.
starPosition
Indicates the spatial location or coordinates of a star relative to a defined reference frame.
- 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_69d889dccf7481909264a1844a2e9100 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e4520f6790819092c36e0e4ecc4cd3 |
completed | April 19, 2026, 3:54 a.m. |
| PD | Predicate disambiguation | batch_69e3b4f5fbcc8190a6ea9639bf5650da |
completed | April 18, 2026, 4:44 p.m. |
| PDg | Predicate description generation | batch_69e3bbb37d148190b7f38599c06594ee |
completed | April 18, 2026, 5:13 p.m. |
Created at: April 10, 2026, 5:48 a.m.