Triple
T87479
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mao Zedong |
E1757
|
entity |
| Predicate | image |
P131
|
FINISHED |
| Object | portrait of Mao Zedong on Tiananmen Gate |
—
|
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: portrait of Mao Zedong on Tiananmen Gate | Statement: [Mao Zedong, image, portrait of Mao Zedong on Tiananmen Gate]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: image Context triple: [Mao Zedong, image, portrait of Mao Zedong on Tiananmen Gate]
-
A.
vision
Indicates that an entity perceives another entity or object visually, using sight.
-
B.
signatureImage
Indicates that an entity has an associated image that visually represents its signature.
-
C.
site
Indicates that one entity is the physical or virtual location where another entity is situated, occurs, or is based.
-
D.
shape
Indicates that one entity has a particular geometric or physical form characterized by the other entity.
-
E.
mediaType
chosen
Indicates the format or category of media associated with an entity, such as text, image, audio, or video.
- 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_69a24c8150408190910a693eb51c1f71 |
completed | Feb. 28, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69a2503d304c8190a0034ffa4a38a501 |
completed | Feb. 28, 2026, 2:17 a.m. |
| PD | Predicate disambiguation | batch_69a24eb6da2c8190a33d144d219f7abe |
completed | Feb. 28, 2026, 2:11 a.m. |
Created at: Feb. 28, 2026, 2:06 a.m.