Triple
T30338320
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Embeddings from Language Models |
E771680
|
entity |
| Predicate | inputUnit |
P168866
|
FINISHED |
| Object | word |
—
|
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: word | Statement: [Embeddings from Language Models, inputUnit, word]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: inputUnit Context triple: [Embeddings from Language Models, inputUnit, word]
-
A.
basedUnit
Indicates that one unit is defined in terms of, or derived from, another more fundamental unit.
-
B.
basicUnitOf
Indicates that one entity serves as the fundamental or smallest constituent unit from which the other entity is composed or defined.
-
C.
baseUnitOf
Indicates that one unit serves as the fundamental reference or standard measurement unit for another derived or related unit.
-
D.
integerUnit
Indicates that one entity serves as the integer-valued unit or base measurement associated with another entity.
-
E.
unitOfMeasure
Indicates that one entity specifies the standard unit in which the quantity or value of another entity is measured.
- 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_69f2248aba24819095bb86480d55b23b |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f681cf69588190b1a6373ddf29dd6a |
completed | May 2, 2026, 10:59 p.m. |
| PD | Predicate disambiguation | batch_69f67603526c81908295a1ece8727c66 |
completed | May 2, 2026, 10:09 p.m. |
| PDg | Predicate description generation | batch_69f676f73c3481909f01fa69851b7298 |
completed | May 2, 2026, 10:13 p.m. |
Created at: April 29, 2026, 7:55 p.m.