Triple
T3658391
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Echidna |
E77589
|
entity |
| Predicate | upperBody |
P50186
|
FINISHED |
| Object | woman |
—
|
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: woman | Statement: [Echidna, upperBody, woman]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: upperBody Context triple: [Echidna, upperBody, woman]
-
A.
torse
Indicates a heraldic depiction where a twisted roll of fabric (the torse) encircles the top of a helmet, typically serving as the base for a crest.
-
B.
highestBody
Indicates that one entity is the tallest or most elevated body (e.g., physical object, celestial body, or structural component) relative to a specified set or context.
-
C.
armType
Indicates the specific kind or configuration of an arm associated with an entity.
-
D.
supportingArms
Indicates that one entity provides military or tactical support, such as firepower or cover, to assist another entity’s operations.
-
E.
isForwardArmOf
Indicates that one object functions as the front or leading arm/extension of another object in a given structure or system.
- 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_69ad85def5cc8190863dccf55a18bebb |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc3d48a2081908ac0f76d548a53ee |
completed | March 8, 2026, 6:45 p.m. |
| PD | Predicate disambiguation | batch_69adb847e9d881909dad2ffd0f3b6c15 |
completed | March 8, 2026, 5:56 p.m. |
| PDg | Predicate description generation | batch_69adb97cdb788190a5ce96b21bd157ab |
completed | March 8, 2026, 6:01 p.m. |
Created at: March 8, 2026, 3:24 p.m.