Triple
T21057387
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | University of Oxford coat of arms |
E518754
|
entity |
| Predicate | tinctureOfBook |
P142667
|
FINISHED |
| Object | argent |
—
|
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: argent | Statement: [University of Oxford coat of arms, tinctureOfBook, argent]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tinctureOfBook Context triple: [University of Oxford coat of arms, tinctureOfBook, argent]
-
A.
tinctureOfInscription
Indicates a relationship where an inscription is embodied, preserved, or represented in the form of a tincture or liquid medium.
-
B.
tinctureOfSun
Indicates a relationship where something is infused, colored, or imbued with the qualities or essence symbolically associated with the sun.
-
C.
tinctureOfLion
Indicates a relationship where something is a medicinal or alchemical preparation (a “tincture”) derived from or associated with a lion.
-
D.
tressureTincture
Indicates the color or pattern (tincture) applied specifically to a tressure in heraldic design.
-
E.
tinctureOfField
Indicates that one entity is a tincture (medicinal extract or solution) derived from, based on, or primarily composed of another entity representing a field or source material.
- 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_69e0b5053ac48190921529544959e906 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e6fd81434c8190aedfddf937f82322 |
completed | April 21, 2026, 4:30 a.m. |
| PD | Predicate disambiguation | batch_69e5dbf9d71881908cd85dfc37db93ca |
completed | April 20, 2026, 7:55 a.m. |
| PDg | Predicate description generation | batch_69e5e2e03d88819086f8b641656ad8b0 |
completed | April 20, 2026, 8:25 a.m. |
Created at: April 16, 2026, 2:37 p.m.