Triple
T32554577
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Khal Drogo |
E832062
|
entity |
| Predicate | skinMarkings |
P8035
|
FINISHED |
| Object | tattoos and war paint (TV series) |
—
|
NE NERFINISHED |
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: tattoos and war paint (TV series) | Statement: [Khal Drogo, skinMarkings, tattoos and war paint (TV series)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: skinMarkings Context triple: [Khal Drogo, skinMarkings, tattoos and war paint (TV series)]
-
A.
skinCharacteristic
chosen
Indicates a relationship where an entity is associated with a particular quality, feature, or condition of its skin.
-
B.
facialMarkings
Indicates that one entity has distinctive marks, patterns, or features on its face in relation to another entity or context.
-
C.
leafMarkings
Indicates the presence, pattern, or characteristics of markings found on the surface of a leaf.
-
D.
colorMarkings
Indicates that one entity has specific color-based markings or patterns in relation to another entity.
-
E.
gravesMarking
Indicates that certain graves serve as markers or indicators for specific individuals, events, or locations.
- 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_69f34926b9848190ace47d2dd0a0de7c |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6c5c95cc481909ab34c9e889a6281 |
completed | May 3, 2026, 3:49 a.m. |
| PD | Predicate disambiguation | batch_69f6bd2a14b081908162923dfbf0a6f4 |
completed | May 3, 2026, 3:12 a.m. |
Created at: May 1, 2026, 1:02 a.m.