Triple
T15232761
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Euron Greyjoy |
E364045
|
entity |
| Predicate | crewCharacteristic |
P107381
|
FINISHED |
| Object | tongueless crew |
—
|
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: tongueless crew | Statement: [Euron Greyjoy, crewCharacteristic, tongueless crew]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: crewCharacteristic Context triple: [Euron Greyjoy, crewCharacteristic, tongueless crew]
-
A.
squadCharacteristic
Indicates that a particular characteristic, trait, or property is attributed to a squad as a whole.
-
B.
crewType
Indicates the specific role or category of crew associated with an entity, such as the type of personnel assigned to operate or support it.
-
C.
crewVariantName
Indicates the specific name or label assigned to a particular variant or version of a crew configuration.
-
D.
featuresCharacterWith
Indicates that one entity (such as a work or product) includes or presents a particular character as part of its content.
-
E.
crewDescription
chosen
Indicates a descriptive statement that characterizes or summarizes the composition, roles, or attributes of a crew involved in an entity or event.
- 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_69d85a0ce24c81909c4d3b6475548c95 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e007d7237081908dc17900ee66b64f |
completed | April 15, 2026, 9:49 p.m. |
| PD | Predicate disambiguation | batch_69deca899d5c8190be4a7c71e1683c69 |
completed | April 14, 2026, 11:15 p.m. |
Created at: April 10, 2026, 3:12 a.m.