Triple
T16230314
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tetracerus |
E393959
|
entity |
| Predicate | hasSkullCharacteristic |
P102283
|
FINISHED |
| Object | frontal bones bearing horn cores |
—
|
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: frontal bones bearing horn cores | Statement: [Tetracerus, hasSkullCharacteristic, frontal bones bearing horn cores]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSkullCharacteristic Context triple: [Tetracerus, hasSkullCharacteristic, frontal bones bearing horn cores]
-
A.
hasSkull
Indicates that an entity possesses or is characterized by the presence of a skull.
-
B.
hasSkullType
Indicates that an entity possesses or is characterized by a specific type or classification of skull.
-
C.
hasSkullDisplayedSeparately
Indicates that the skull of an individual or specimen is displayed separately from the rest of its remains or body.
-
D.
skullUsage
Indicates how a skull is used, applied, or functionally involved in a particular context or activity.
-
E.
skullOrnamentation
chosen
Indicates that an entity has decorative or structural features specifically adorning or modifying the skull.
- 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_69d87f204df88190a8f88923decf9835 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e23d29438c81909aa2724cc47bb959 |
completed | April 17, 2026, 2:01 p.m. |
| PD | Predicate disambiguation | batch_69e219e94a448190b73a4e6aa374eb4a |
completed | April 17, 2026, 11:30 a.m. |
Created at: April 10, 2026, 5:03 a.m.