Triple
T20873118
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Malayan tapir |
E513943
|
entity |
| Predicate | neonateCoatPattern |
P78897
|
FINISHED |
| Object | brown with white stripes and spots |
—
|
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: brown with white stripes and spots | Statement: [Malayan tapir, neonateCoatPattern, brown with white stripes and spots]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: neonateCoatPattern Context triple: [Malayan tapir, neonateCoatPattern, brown with white stripes and spots]
-
A.
camouflagePattern
Indicates that one entity has a surface or visual design intended to conceal it by blending with its surroundings or disrupting its outline.
-
B.
usesTricolorPattern
Indicates that an entity employs a three-color pattern as a defining or characteristic design element.
-
C.
distinguishingCoatFeature
chosen
Indicates a characteristic of an entity’s coat (such as pattern, color, or marking) that serves to distinguish it from others.
-
D.
textileFeature
Indicates a characteristic, property, or notable aspect associated with a textile or fabric.
-
E.
airingPattern
Indicates the recurring schedule or pattern according to which something (such as a program or content) is broadcast or made available.
- 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_69e0b4f675cc8190b4e745225b62eb66 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c46639308190a616193f3975d453 |
completed | April 21, 2026, 12:27 a.m. |
| PD | Predicate disambiguation | batch_69e5c9a8dc148190b33ff51894e2a8f9 |
completed | April 20, 2026, 6:37 a.m. |
Created at: April 16, 2026, 12:45 p.m.