Triple
T33693094
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eurasian hoopoe |
E863233
|
entity |
| Predicate | crestMarkings |
P171798
|
FINISHED |
| Object | black tips |
—
|
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: black tips | Statement: [Eurasian hoopoe, crestMarkings, black tips]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: crestMarkings Context triple: [Eurasian hoopoe, crestMarkings, black tips]
-
A.
coatMarkings
Indicates how an entity’s coat is patterned or marked, such as stripes, spots, or other distinctive visual markings.
-
B.
armorMarkings
Indicates that one entity bears specific markings, patterns, or insignia on its armor in relation to another entity or context.
-
C.
colorOfTrailMarkings
Indicates the relationship specifying what color the trail’s markings are.
-
D.
billMarkings
Indicates a relationship where specific markings or patterns are present on or associated with a bill (such as a beak or financial document).
-
E.
colorMarkings
chosen
Indicates that one entity has specific color-based markings or patterns in relation to another 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_69f3498723a08190ac034339cc78eade |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f6fa86c4308190b13345c7517a8ddf |
completed | May 3, 2026, 7:34 a.m. |
| PD | Predicate disambiguation | batch_69f6f96dd4c8819093d6a7bd046a9ad5 |
completed | May 3, 2026, 7:29 a.m. |
Created at: May 1, 2026, 1:43 a.m.