Triple
T17217353
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sir Nicholas de Mimsy-Porpington |
E417886
|
entity |
| Predicate | neckInjuryDescription |
P23450
|
FINISHED |
| Object | head attached by a small amount of skin and sinew |
—
|
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: head attached by a small amount of skin and sinew | Statement: [Sir Nicholas de Mimsy-Porpington, neckInjuryDescription, head attached by a small amount of skin and sinew]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: neckInjuryDescription Context triple: [Sir Nicholas de Mimsy-Porpington, neckInjuryDescription, head attached by a small amount of skin and sinew]
-
A.
neckJoint
Indicates a joint or connection located at or functioning as the neck between two body parts or structural elements.
-
B.
injuredBodyPart
Indicates that an entity has sustained an injury specifically affecting a particular body part.
-
C.
injuryType
chosen
Indicates the specific kind or category of injury associated with an entity or event.
-
D.
neckCharacteristic
Indicates that an entity has a specific attribute, feature, or quality related to its neck.
-
E.
injuriesApprox
Indicates an approximate or estimated number or extent of injuries associated with an event or entity.
- 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_69d886d779488190b131369541c04e7d |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e42dda6e6c81908dd96f653cd2cba0 |
completed | April 19, 2026, 1:20 a.m. |
| PD | Predicate disambiguation | batch_69e3831e354881908c5505ffd15c84e9 |
completed | April 18, 2026, 1:11 p.m. |
Created at: April 10, 2026, 5:38 a.m.