Triple
T1261239
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eagle (10-dollar gold coin) |
E12504
|
entity |
| Predicate | submultipleRelation |
P26378
|
FINISHED |
| Object | 1 half eagle = 5 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 half eagle = 5 dollars | Statement: [Eagle (10-dollar gold coin), submultipleRelation, 1 half eagle = 5 dollars]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: submultipleRelation Context triple: [Eagle (10-dollar gold coin), submultipleRelation, 1 half eagle = 5 dollars]
-
A.
belongsToSubfamily
Indicates that one entity is a member of, or classified within, a specific subfamily of another entity.
-
B.
hasSubcategoryRelation
Indicates that one category is a more specific subdivision or subset of another broader category.
-
C.
subclassOf
Indicates that one class is a more specific type of another class, inheriting its characteristics as a subset of it.
-
D.
subordinateTo
Indicates that one entity holds a lower rank, status, or authority and is subject to the control, direction, or oversight of another entity.
-
E.
supportsRelation
Indicates that one entity provides assistance, endorsement, or structural backing to another entity or its activity.
- 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.