Triple
T1261240
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eagle (10-dollar gold coin) |
E12504
|
entity |
| Predicate | multipleRelation |
P26379
|
FINISHED |
| Object | 1 double eagle = 20 dollars |
—
|
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: 1 double eagle = 20 dollars | Statement: [Eagle (10-dollar gold coin), multipleRelation, 1 double eagle = 20 dollars]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: multipleRelation Context triple: [Eagle (10-dollar gold coin), multipleRelation, 1 double eagle = 20 dollars]
-
A.
relatedTo
Indicates a general, non-specific relationship or association exists between two entities.
-
B.
datumRelation
Indicates a relationship where one piece of data is connected to, derived from, or otherwise associated with another piece of data.
-
C.
relatedField
Indicates that one field, topic, or area of study is connected or relevant to another in subject matter or application.
-
D.
supportsRelation
Indicates that one entity provides assistance, endorsement, or structural backing to another entity or its activity.
-
E.
relationshipType
Indicates the specific kind of relationship that exists between two or more entities.
- 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_69a4933352e08190ac617291985e76c0 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a4bfc64e648190b9c4f980eb8168aa |
completed | March 1, 2026, 10:37 p.m. |
| PD | Predicate disambiguation | batch_69a4bb6eefbc81908dddd7d2ef368186 |
completed | March 1, 2026, 10:19 p.m. |
| PDg | Predicate description generation | batch_69a4bd98b62c8190a5f6710345c0537d |
completed | March 1, 2026, 10:28 p.m. |
Created at: March 1, 2026, 7:50 p.m.