Triple
T33775256
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sandor Clegane |
E865497
|
entity |
| Predicate | relationToGregorClegane |
P206671
|
FINISHED |
| Object | younger brother |
—
|
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: younger brother | Statement: [Sandor Clegane, relationToGregorClegane, younger brother]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationToGregorClegane Context triple: [Sandor Clegane, relationToGregorClegane, younger brother]
-
A.
relationToStephenI
Indicates a familial or social relationship that an entity has specifically with Stephen I.
-
B.
relationshipToGregorSamsa
Indicates the specific familial, social, or personal relationship that one entity has to Gregor Samsa.
-
C.
relationToAndrewMartin
Indicates a relationship that specifies how one entity is connected or related to Andrew Martin.
-
D.
relationshipToKingHamlet
Indicates the specific familial or social relationship an entity has to King Hamlet.
-
E.
relationshipToHomer
Indicates the specific familial or social relationship that one entity has to Homer.
- 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_69f3498df6f88190bf9647ea4e4a956e |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a037e0953908190b2930b3c06a40129 |
completed | May 12, 2026, 7:22 p.m. |
| PD | Predicate disambiguation | batch_6a0379f6c3308190b954f7810214ceed |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037e07fe4481909ca21eae7a941ee7 |
completed | May 12, 2026, 7:22 p.m. |
Created at: May 1, 2026, 1:45 a.m.