Triple
T32847952
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dulong people |
E840154
|
entity |
| Predicate | facialTattooing |
P125456
|
FINISHED |
| Object | traditionally practiced on women |
—
|
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: traditionally practiced on women | Statement: [Dulong people, facialTattooing, traditionally practiced on women]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: facialTattooing Context triple: [Dulong people, facialTattooing, traditionally practiced on women]
-
A.
facialMarkings
chosen
Indicates that one entity has distinctive marks, patterns, or features on its face in relation to another entity or context.
-
B.
hasFacePaintColor
Indicates that an entity’s face paint is of a specified color.
-
C.
hasTattoo
Indicates that one entity bears a tattoo on their body.
-
D.
faceType
Indicates the specific shape or structural category of a face that an entity possesses or is characterized by.
-
E.
notableTattoo
Indicates that an entity has a tattoo that is distinctive, prominent, or otherwise noteworthy.
- 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_69f349412c78819084459850e11d29f7 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6ce736b408190b7266820b6ec3cd1 |
completed | May 3, 2026, 4:26 a.m. |
| PD | Predicate disambiguation | batch_69f6cc1667a48190b42684f6ec22dae9 |
completed | May 3, 2026, 4:16 a.m. |
Created at: May 1, 2026, 1:17 a.m.