Triple
T34957381
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Miral Paris |
E1008154
|
entity |
| Predicate | hasKlingonForeheadRidges |
P59759
|
FINISHED |
| Object | yes (adult depiction) |
—
|
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: yes (adult depiction) | Statement: [Miral Paris, hasKlingonForeheadRidges, yes (adult depiction)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasKlingonForeheadRidges Context triple: [Miral Paris, hasKlingonForeheadRidges, yes (adult depiction)]
-
A.
hasRidges
chosen
Indicates that one entity possesses raised, linear or patterned ridges on its surface or structure in relation to another entity or context.
-
B.
hasSkullFeature
Indicates that an entity possesses a specific characteristic, structure, or attribute of the skull.
-
C.
hasPhysicalFeature
Indicates that one entity possesses or exhibits a specific physical characteristic or feature of another entity.
-
D.
hasOssicones
Indicates that an entity possesses ossicones, the horn-like bony protuberances on the head.
-
E.
hasScar
Indicates that one entity bears or possesses a scar on its body.
- 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_69f76dc69564819099e9e78aed6ff0a6 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f78710282c81909146dc0be91e983f |
completed | May 3, 2026, 5:34 p.m. |
| PD | Predicate disambiguation | batch_69f784162134819098413482ef52042f |
completed | May 3, 2026, 5:21 p.m. |
Created at: May 3, 2026, 4 p.m.