Triple
T13051543
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cardinal |
E327459
|
entity |
| Predicate | vestment |
P55876
|
FINISHED |
| Object | red biretta |
—
|
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: red biretta | Statement: [Cardinal, vestment, red biretta]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: vestment Context triple: [Cardinal, vestment, red biretta]
-
A.
investment
Indicates a relationship where one party allocates resources (such as money, time, or effort) into something with the expectation of future benefit or return.
-
B.
vestments
chosen
Indicates that one entity is wearing or is ceremonially clothed in special religious or official garments associated with a role or office.
-
C.
investmentType
Indicates the specific category or nature of an investment associated with an entity or transaction.
-
D.
investmentScope
Indicates the range or boundaries of activities, assets, or sectors that an investment is intended or allowed to cover.
-
E.
investmentTarget
Indicates that one entity is the object or recipient of another entity’s investment.
- 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_69d8076e64308190904fb5c93517c901 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d98a9829b48190b23624b6b3df4600 |
completed | April 10, 2026, 11:41 p.m. |
| PD | Predicate disambiguation | batch_69d9803aca4c8190b1015cd159cc47a9 |
completed | April 10, 2026, 10:56 p.m. |
Created at: April 9, 2026, 8:57 p.m.