Triple
T9286409
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Babyrousa babyrussa |
E223403
|
entity |
| Predicate | tuskGrowthDirection |
P87400
|
FINISHED |
| Object | grow upward through the snout |
—
|
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: grow upward through the snout | Statement: [Babyrousa babyrussa, tuskGrowthDirection, grow upward through the snout]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tuskGrowthDirection Context triple: [Babyrousa babyrussa, tuskGrowthDirection, grow upward through the snout]
-
A.
hasTusk
Indicates that an entity possesses one or more tusks as a physical feature.
-
B.
antlerType
Indicates the specific kind or classification of antlers that an entity possesses or is associated with.
-
C.
hasTailShape
Indicates that an entity possesses a tail with a specific shape or form.
-
D.
tailCharacteristic
Indicates that an entity possesses a particular property, feature, or quality specifically related to its tail.
-
E.
snoutType
Indicates the type or form of an entity’s snout in relation to its overall morphology.
- F. None of above. chosen
Provenance (4 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_69ca8422ddf881908a3f8f876c9f53aa |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd0821b1108190b16e9570b09a14de |
completed | April 1, 2026, 11:57 a.m. |
| PD | Predicate disambiguation | batch_69cc7a576ec88190bbb787eb82e2e539 |
completed | April 1, 2026, 1:52 a.m. |
| PDg | Predicate description generation | batch_69cc94b796788190816b71b1e9996288 |
completed | April 1, 2026, 3:44 a.m. |
Created at: March 30, 2026, 7:35 p.m.