Triple
T4160752
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kocher forceps |
E91526
|
entity |
| Predicate | typicalTipConfiguration |
P5084
|
FINISHED |
| Object | one tooth on one jaw and two teeth on the opposite jaw |
—
|
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: one tooth on one jaw and two teeth on the opposite jaw | Statement: [Kocher forceps, typicalTipConfiguration, one tooth on one jaw and two teeth on the opposite jaw]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalTipConfiguration Context triple: [Kocher forceps, typicalTipConfiguration, one tooth on one jaw and two teeth on the opposite jaw]
-
A.
typicalBase
Indicates that one entity serves as the standard or most representative base or foundation for another entity in typical or common cases.
-
B.
typicalIn
Indicates that something commonly occurs, appears, or is found within a given context, category, or environment.
-
C.
typicalPractice
Indicates that an action, behavior, or method is commonly or customarily done in a given context or by a given group.
-
D.
typicalFeatures
chosen
Indicates that the related entities are characteristic or commonly occurring features or attributes of something.
-
E.
typicalSeat
Indicates the usual or standard seating position or location associated with an entity in a given context.
- 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_69aed9626ebc8190a39de631788bea3e |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af0321eee88190871c1d4bf44a5007 |
completed | March 9, 2026, 5:28 p.m. |
| PD | Predicate disambiguation | batch_69af018dc90c8190a754b1bfbc802e80 |
completed | March 9, 2026, 5:21 p.m. |
Created at: March 9, 2026, 3:44 p.m.