Triple
T3524168
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Titanosauria |
E74497
|
entity |
| Predicate | dermalArmor |
P11885
|
FINISHED |
| Object | osteoderms in many taxa |
—
|
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: osteoderms in many taxa | Statement: [Titanosauria, dermalArmor, osteoderms in many taxa]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: dermalArmor Context triple: [Titanosauria, dermalArmor, osteoderms in many taxa]
-
A.
armour
Indicates that an entity provides protective covering or defense for another entity.
-
B.
armourThickness
Indicates the measured thickness of an entity’s protective armor in the context of defense or shielding.
-
C.
armourBelt
Indicates a relationship where an armour belt is equipped on, attached to, or associated with an entity (such as a character, vehicle, or structure) as protective gear.
-
D.
sideArmorThickness
Indicates the thickness of an object's armor specifically along its sides.
-
E.
armorType
chosen
Indicates the specific category or classification of protective armor associated with 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_69ad85d0c5488190a3d8e02ebd01a1aa |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adbc68b15881909b407486946ec3c5 |
completed | March 8, 2026, 6:14 p.m. |
| PD | Predicate disambiguation | batch_69adae121a048190b03825a001d21f49 |
completed | March 8, 2026, 5:12 p.m. |
Created at: March 8, 2026, 3:19 p.m.