Triple
T34869005
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | drill (Mandrillus leucophaeus) |
E1005096
|
entity |
| Predicate | facialColoration |
P137296
|
FINISHED |
| Object | dark face with lighter muzzle areas |
—
|
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: dark face with lighter muzzle areas | Statement: [drill (Mandrillus leucophaeus), facialColoration, dark face with lighter muzzle areas]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: facialColoration Context triple: [drill (Mandrillus leucophaeus), facialColoration, dark face with lighter muzzle areas]
-
A.
hasFacialSkinColor
chosen
Indicates that one entity has a specific facial skin color characterized or attributed by another entity.
-
B.
facialMarkings
Indicates that one entity has distinctive marks, patterns, or features on its face in relation to another entity or context.
-
C.
facialDiscColor
Indicates the color or coloration pattern of an entity’s facial disc.
-
D.
skinCharacteristic
Indicates a relationship where an entity is associated with a particular quality, feature, or condition of its skin.
-
E.
pigmentation
Indicates the presence, type, or degree of coloration in or on an entity.
- 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_69f76dbb678081909a247b9b5e1a73ac |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f782f4f10081908f97f6d0d2dbeec7 |
completed | May 3, 2026, 5:16 p.m. |
| PD | Predicate disambiguation | batch_69f780ff71cc8190a67e71076fbad81a |
completed | May 3, 2026, 5:08 p.m. |
Created at: May 3, 2026, 4 p.m.