Triple
T14706828
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | House Arryn |
E345449
|
entity |
| Predicate | words |
P67723
|
FINISHED |
| Object | As High as Honor |
—
|
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: As High as Honor | Statement: [House Arryn, words, As High as Honor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: words Context triple: [House Arryn, words, As High as Honor]
-
A.
word1
Indicates that there is a first word in a sequence or pair that participates in the specified relationship.
-
B.
writingMeaning
Indicates that one entity expresses or conveys a particular meaning through writing about another entity or topic.
-
C.
usesWord
chosen
Indicates that one entity employs, contains, or makes use of a particular word in its expression, content, or communication.
-
D.
writingTool
Indicates that one entity serves as a tool or instrument used by another entity for the act of writing.
-
E.
letters
Indicates that one entity is composed of, represented by, or associated with specific alphabetic characters or written symbols.
- 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_69d822e4a8c08190a155df736bb7bc13 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb609965081908f654bcb9eaaa145 |
completed | April 14, 2026, 9:47 p.m. |
| PD | Predicate disambiguation | batch_69de657c57ec8190ae0b9bb79a514566 |
completed | April 14, 2026, 4:04 p.m. |
Created at: April 10, 2026, 1:28 a.m.