Triple
T14779978
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sandor Clegane |
E347365
|
entity |
| Predicate | causeOfScars |
P14656
|
FINISHED |
| Object | burned by his brother Gregor Clegane |
—
|
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: burned by his brother Gregor Clegane | Statement: [Sandor Clegane, causeOfScars, burned by his brother Gregor Clegane]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: causeOfScars Context triple: [Sandor Clegane, causeOfScars, burned by his brother Gregor Clegane]
-
A.
causeOfInjury
chosen
Indicates that one entity is the source or reason that another entity sustained an injury.
-
B.
causeOf
Indicates that one entity brings about, produces, or is responsible for the occurrence or existence of another entity or event.
-
C.
causeStatus
Indicates that one entity brings about, initiates, or is responsible for a particular state or condition in another entity.
-
D.
hasScar
Indicates that one entity bears or possesses a scar on its body.
-
E.
skinCharacteristic
Indicates a relationship where an entity is associated with a particular quality, feature, or condition of its skin.
- 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_69d822e9b9e08190bedcc31a163fda82 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deca9c7cac8190ba900df95e42e318 |
completed | April 14, 2026, 11:15 p.m. |
| PD | Predicate disambiguation | batch_69de8c090d1081909b5a9bf437499d6c |
completed | April 14, 2026, 6:48 p.m. |
Created at: April 10, 2026, 1:31 a.m.