Triple
T29444705
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Big Shave |
E746815
|
entity |
| Predicate | hasBloodEffects |
P123084
|
FINISHED |
| Object | practical effects |
—
|
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: practical effects | Statement: [The Big Shave, hasBloodEffects, practical effects]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBloodEffects Context triple: [The Big Shave, hasBloodEffects, practical effects]
-
A.
hasBlood
Indicates that one entity possesses or contains the blood of another entity.
-
B.
bloodStatus
Indicates the classification of an entity based on the type or purity of its blood or lineage.
-
C.
obtainsBloodFrom
Indicates that one entity receives or collects blood from another entity.
-
D.
hasBloodPigment
Indicates that an organism possesses a specific pigment in its blood responsible for coloration and often for oxygen transport.
-
E.
hasEffectIn
chosen
Indicates that one entity produces, causes, or exerts an effect within a specified context, system, or environment.
- 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_69f0a7a230488190b44a97fe3d16f731 |
completed | April 28, 2026, 12:27 p.m. |
| NER | Named-entity recognition | batch_69f66b203bd481908eb67bc9f7e0e5a9 |
completed | May 2, 2026, 9:22 p.m. |
| PD | Predicate disambiguation | batch_69f66339175c819080bd70f0ff7057b1 |
completed | May 2, 2026, 8:48 p.m. |
Created at: April 28, 2026, 3:26 p.m.