Triple
T2545276
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Swiss Guard |
E57882
|
entity |
| Predicate | modernUniformIntroduced |
P39475
|
FINISHED |
| Object | 1914 |
—
|
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: 1914 | Statement: [Swiss Guard, modernUniformIntroduced, 1914]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: modernUniformIntroduced Context triple: [Swiss Guard, modernUniformIntroduced, 1914]
-
A.
wearsUniformSimilarTo
Indicates that one entity wears a uniform that is similar in appearance or style to the uniform worn by another entity.
-
B.
militarySize
Indicates the total number of personnel in a military force, typically including active-duty members and sometimes reserves.
-
C.
militaryEquivalence
Indicates that two or more entities possess comparable military capabilities, strength, or strategic power such that neither holds a clear military advantage over the other.
-
D.
hasMilitarySignificanceSince
Indicates that something has held military importance or strategic value starting from a specified point in time.
-
E.
wearsOnUniform
Indicates that an item is part of and is worn as a component of a uniform.
- 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_69ab4a5212d88190b989ce129f2ad87f |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd2c285288190b41fc0188879623a |
completed | March 7, 2026, 7:24 a.m. |
| PD | Predicate disambiguation | batch_69abd0c63964819092d5f578195ae8dd |
completed | March 7, 2026, 7:16 a.m. |
| PDg | Predicate description generation | batch_69abd1c7b6e48190be9a0c31069df797 |
completed | March 7, 2026, 7:20 a.m. |
Created at: March 6, 2026, 9:47 p.m.