Triple
T4160743
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kocher forceps |
E91526
|
entity |
| Predicate | hasLengthRange |
P54172
|
FINISHED |
| Object | approximately 14 cm to 20 cm |
—
|
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: approximately 14 cm to 20 cm | Statement: [Kocher forceps, hasLengthRange, approximately 14 cm to 20 cm]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLengthRange Context triple: [Kocher forceps, hasLengthRange, approximately 14 cm to 20 cm]
-
A.
hasBodyLengthRange
Indicates the range of possible body lengths associated with an entity, typically expressed as a minimum and maximum value.
-
B.
hasMinimumLength
Indicates that the length of an entity (such as a sequence, string, or collection) is greater than or equal to a specified minimum value.
-
C.
hasMaxLengthApprox
Indicates that something has a maximum length that is approximately equal to a specified value, allowing for some tolerance or imprecision.
-
D.
hasRange
Indicates that a property or relation is constrained to take its values from a specified class, type, or value set.
-
E.
hasFieldLength
Indicates that an entity possesses a field whose length (such as number of characters or size) is specified or constrained.
- F. None of above. chosen
Provenance (4 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. |
| PDg | Predicate description generation | batch_69af0320775c8190b90d80f512060f1c |
completed | March 9, 2026, 5:28 p.m. |
Created at: March 9, 2026, 3:44 p.m.